Pi Sigma Alpha Undergraduate Journal of Politics Spring 2019 by psajournalou

Vol. XIX No. 1

Spring 2019

PI SIGMA ALPHA

Undergraduate Journal of Politics

Oakland University

Pi Sigma Alpha Undergraduate Journal of Politics

The Pi Sigma Alpha Undergraduate Journal of Politics (ISSN 1556-2034) is published biannually by the Nu Omega Chapter of Pi Sigma Alpha, Oakland University, Department of Political Science, Varner Hall, Room 418, 371 Varner Drive, Rochester, MI 48309-4485. The Journal is funded by Pi Sigma Alpha, the National Political Science Honor Society, 1527 New Hampshire Avenue, NW, Washington, DC 20036, http://www. pisigmaalpha.org. The Pi Sigma Alpha Undergraduate Journal of Politics was founded in the Spring of 2001 by Delta Omega Chapter of Pi Sigma Alpha at Purdue University, under the name The American Undergraduate Journal of Politics and Government. With the sponsorship of Pi Sigma Alpha, the National Political Science Honor Society, the name of the Journal was changed to The Pi Sigma Alpha Undergraduate Journal of Politics as of the Fall 2004 edition. Electronic editions of the Journal are available online at http://www.psajournal.org. For further information, please contact Dr. Terri Towner at Oakland University (towner@ oakland.edu). All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the written permission of the editors and faculty advisors of The Pi Sigma Alpha Undergraduate Journal of Politics. The Pi Sigma Alpha Undergraduate Journal of Politics and content appearing there-in is copyrighted by Pi Sigma Alpha. While holding these rights, Pi Sigma Alpha does not exert editorial or other control over the content of the Journal or the decisions or actions of its staff in the course of normal business operations. As such, Pi Sigma Alpha neither asserts nor accepts responsibility for the content or actions of staff of the publication in the normal course of business as the customs and usages of the law allow. All assertions of fact and statements of opinion are solely those of the authors. They do not necessarily represent the views of Pi Sigma Alpha, the National Political Science Honor Society, the Editorial Board, the Advisory Board, the Faculty Advisors, Oakland University, or its faculty and administration. COPYRIGHT ÂŠ 2019 PI SIGMA ALPHA. ALL RIGHTS RESERVED

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Vol. XIX No. 1 • Spring 2019

The Pi Sigma Alpha Undergraduate Journal of Politics Spring 2019 Volume XIX

Number 1 Thirty-Seventh Edition

Hannah Gorosh Christina Pearl Walker Tanir-Vefa Avci Dr. Terri L. Towner

Scheduling/Content Editor Outreach Editor Cover Designer Faculty Advisor and Editor

Editorial Board Jacob Adams Ian Anderson Alex Bertges Natalie Cordell Ghazi Ghazi Hannah Gorosh Brooke Hebb Chase Lindenthal

Marco Micheletta Melinda Movious Erica Potter Brian Quinn Christina Pearl Walker Hunter Willis Johnathan Wertheimer

Advisory Board Dr. Robert Alexander Dr. Nicole Asmussen Mathew Dr. Cristian Cantir Dr. Rosalee Clawson Dr. Erik Cleven Dr. Cody Eldredge Dr. Alan Epstein Dr. Stephen Farnsworth Dr. Megan Hershey Dr. Dwaine Jengelley Dr. Baris Kesgin Dr. Kellee Kirkpatrick Dr. John Klemanski

Dr. Jeanine Kraybill Dr. Paulette Kurzer Dr. Laura Landolt Dr. Anthony Nowns Dr. Daniel O’Neill Dr. Zoe Oxley Dr. Ronald Rapoport Dr. Jo Reger Dr. Jaime Settle Dr. Harry “Neil” Strine Dr. Peter Trumbore Dr. Kali Wright-Smith

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Editorâ&#x20AC;&#x2122;s Preface to the Spring Edition The Pi Sigma Alpha Journal of Undergraduate Politics would first and foremost like to acknowledge all those individuals and institutions which make the publication of this Journal possible semester after semester and year after year. The Journal has continued to grow in terms of submissions, quality, and prestige. Submissions to the Spring 2019 issue well-exceeded over 100 manuscripts, representing a diverse array of topics. We greatly appreciate all those who have submitted their work to the Journal in the hope of being published. The articles published herein exemplify a high quality sample of the types of undergraduate research being conducted across the country. Although the publication is a completely student-run endeavor, the efforts of the student Editorial Board are guided and supported by a number of individuals and institutions which we would like to thank. First, we would like to thank the Pi Sigma Alpha Executive Council and Executive Committee whose vision and financial support has maintained the quality and direction of the Journal. Second, we extend our appreciation to the Oakland University College of Arts and Sciences and the Political Science Department. Third, we would like to thank the Faculty Advisory board whose constructive reviews ensure the articles published herein meet a consistent standard of quality. Finally, we extend tremendous thanks to Editorial Board Faculty Advisor Terri Towner, who has dedicated her time and energy to ensure the integrity of the Journal continues to exceed the standards of excellence set by the editors of its previous editions. The Editorial Board at Oakland University is proud to present the Spring issue which contains a wellrounded set of articles with varied methodological approaches and topical matter. The publishing process for the Spring issue followed a relatively smooth path from submission to publication, and the Nu Omega Chapter and Oakland University wish the readers of this issue a similarly enjoyable time. Best, The Editors

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Vol. XIX No. 1 • Spring 2019

Submission of Manuscripts The Journal accepts manuscripts from undergraduates of any class and major. Members of Pi Sigma Alpha are especially encouraged to enter their work. We strive to publish papers of the highest quality in all areas of political science. Generally, selected manuscripts have been well-written works with a fully developed thesis and strong argumentation stemming from original analysis. Authors may be asked to revise their work before being accepted for publication. Submission deadlines are October 1st for the Fall edition and February 1st for the Spring edition. Manuscripts are accepted on a rolling basis; therefore early submissions are strongly encouraged. To submit your work, please email psajournalou@gmail.com with an attached Word document of the manuscript. Please include your name, university and contact details (mailing address, email address, and phone number) in a separate document. Submitted manuscripts must include a short abstract (approximately 150 words), citations and references that follow the APSA Style Manual for Political Science. Please do not exceed the maximum page length of 35 double-spaced pages, which includes references, tables, figures, and appendices. The Journal is a student-run enterprise with editors and an Editorial Board that are undergraduate students and Pi Sigma Alpha members at Oakland University. The Editorial Board relies heavily on the help of our Faculty Advisory Board consisting of political science faculty from across the nation, including members of the Pi Sigma Alpha Executive Council. Due to the time committed to the manuscript review process, we would like to remind students to submit only one manuscript at a time. Please direct any questions about submissions or the Journal’s upcoming editions to our editors at psajournalou@gmail.com.

Pi Sigma Alpha Undergraduate Journal of Politics

Contents Hours into Votes: Underemployment at the Ballot Box .................................................................................. 7 Devon Moffett, Northern Kentucky University Polarization and Party Cohesion in Campaign Messaging: Do Female Republican Senate Candidates Rely More Heavily on Party Cohesion Messaging in Campaign Advertisements?........................ 16 Allison R. Cyrus, University of Tennessee, Chattanooga Reluctance to Express Vote Choice among Ohioans during the 2016 U.S. Presidential Election ................... 32 Andrew Henthorn, Baldwin Wallace University Analyzing the Potency of Lawfare in the Israeli-Palestinian Conflict.............................................................. 45 Jack Hostager, University of Pennsylvania Confident Women, Compassionate Leaders: The Effect of Single-Sex Education on Female Empowerment in Uganda............................................................................................................................. 57 Abigail Nolan, Saint Anselm College

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Hours into Votes: Underemployment at the Ballot Box

Hours into Votes: Underemployment at the Ballot Box Devon Moffett, Northern Kentucky University By many counts, underemployment affects more voters than unemployment, and yet the statistic has not been analyzed in economic voting models. As such, this paper asks: how does underemployment affect electoral outcomes? An independently constructed dataset covering presidential and senatorial elections from 2004 to 2016 was used to test various possible influences of underemployment on electoral outcomes. It is found that underemployment provides a consistent Republican advantage, that there is some evidence of voters punishing incumbents for underemployment alongside this advantage, and that midterms influence how voters react to underemployment.

INTRODUCTION hile it is not quite as prominent a concept as unemployment, underemployment remains a constant presence in the considerations of voters. It is simply intuitive that in poor economic times, one is likely either to fall out of work or be given less work than desired. Even in more prosperous times, official statistics point towards a greater likelihood of having too few hours rather than none. Nevertheless, underemployment has thus far failed to gain a place in the models of economic voting presented by researchers. This is perhaps because detailed indexes of underemployment have not been available until recently. In light of this situation, it is important to analyze the possible role of this alternative employment status. This paper will ask the following question: how does underemployment affect electoral outcomes? To answer this question, the four primary stances on economic voting — those of pocketbook voting, sociotropic voting, reward and punishment, and issue identification – will first be considered. Of the four approaches, the school of issue identification will be chosen as the most compelling for future research. With this understanding of economic voting established, this study will hypothesize that underemployment will result in a Democratic advantage, a reciprocal Republican disadvantage will lack a direct punishment effect, and will be influenced by different electoral contexts. Three regressions will be estimated, both on presidential and senatorial elections between 2004 and 2016, to test these hypotheses. Based on these models, the first two hypotheses reveal a reversal of expectations with findings of a Republican advantage but maintain the fundamental logic of the issue identification school. The third hypothesis offers evidence of a punishment effect alongside a partisan advantage. Analysis of the final two hypotheses affirms that the effects of underemployment change in midterms, but that this relationship also manifests differently than expected. With these conclusions in mind, it can be

inferred that underemployment has a significant role to play in future models of economic voting.

Background and Literature

To understand the question of underemployment’s effects, it is important to grasp the general question of how economic voting works. The responses to this inquiry can be split into four primary bodies of scholarship. The first two — pocketbook voting and sociotropic voting — focus on why economic voting happens. The pocketbook voting school presents the argument that political outcomes will be shaped by the economic experiences of voters (Kiewiet 1981; Mutz 1993). Scholars of the sociotropic voting tradition instead assert the view that collective-level perceptions of economic performance rather than personal conditions will translate in political choices (Funk and García-Monet 1997; Rogers 2014). The latter two bodies of scholarship are concerned with how economic voting manifests itself and are the reward and punishment perspective and the issue identification approach. The reward and punishment school of thought predicts that voters will use economic perceptions to evaluate incumbent candidates and parties (Fiorina 1978; Markus 1988). Finally, the issue identification trend of literature argues that voters view economic conditions in terms of partisan issues and make voting choices based on preferred responses (Grafstein 2005; Wright 2012).

Pocketbook Voting

The common premise among pocketbook voting literature is that voters ultimately make political judgments based on personal economic circumstances. In this view, those who experience economic vulnerability will use that experience as a path to making political judgments (Lewis-Beck 1985; Petrow and Vercelloti 2016). Scholars in this tradition can support either a direct or indirect path by which this relationship is realized, but the unifying feature is an insistence on the importance of personal experience.

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The foundational research on economic voting started from the premise of a rational voter who evaluates his or her own economic situation and then uses that evaluation to choose a candidate that can provide the greatest material benefit. This basic approach can be seen in Kiewiet’s (1981) research on policy-oriented voting, where it was found that personal experience with unemployment was a good predictor of the vote choice of survey respondents. The translation of economic circumstances to political judgments was not perfect, however, so early research on pocketbook voting opened up a discussion of what mediated the relationship between the two. A good example of the pocketbook scholarship on this question is found in the work of Mutz (1993). Mutz’s (1993) finding was that personal economic experiences had a direct impact on high knowledge voters who had a sophisticated enough understanding to link their experiences with national politics. On the other hand, the route that the less knowledgeable took to politicizing their experience was indirect. Personal experiences were utilized to interpret national conditions, which only then were attributed to political actors. The commonality between high and low knowledge voters, however, was that they both relied on personal and interpersonal experience to interpret unemployment. This basic premise was again tested in Lau and Helman’s (2009) research, which showed that contextual variables representing social and informational environment had a significant impact on the magnitude of self-interest effects. A common criticism of pocketbook voting, however, was presented by Feldman (1982; 1984). He contended that even considering environmental variables, many analyses of the practical effects of personal economic circumstances show a minor influence; such findings seemed to show that the mythos of economic individualism or some other mechanism was largely mitigating voters’ ability to link personal and political circumstances. Pocketbook voting scholars, such as Petrow and Vercelloti (2016), responded to this argument by emphasizing a distinction between the self-interest projected by researchers and the self-interest perceived by voters. A misattribution of self-interest may make researchers assume that voters are not linking personal circumstances to political stances where in fact they are. After accounting for this disconnect, Petrow and Vercelloti (2016) found evidence of a significant influence of self-interest. Another common critique of pocketbook voting was present in Sears and Lua’s (1983) argument that the purported influence of personal experiences was the product of posthoc rationalizations of voting decisions. Research, such as that of Lewis-Beck (1985), contradicted this view of personal experience being a methodological error, however. Through the use of CPS-SRC surveys for presidential and congressional elections from 1956 to 1982, Lewis-Beck (1985) was able to show that the effects of personal interest were consistent across surveys in both a retroactive and proactive context. 8

Sociotropic Voting

The view expressed by the sociotropic voting school emphasizes the influence of broader social conditions in political considerations. From this perspective, the economic influence on voting choices will be felt primarily through perspectives on macroeconomic conditions (Dickerson 2016; Ragusa and Tarpey 2016). Some debate has been held about the incorporation of self-interest and non-national effects, but scholars of this school are united in their assertion that collective judgments are the primary determinates of economic voting. An early example of sociotropic voting literature is found in the research of Kinder and Kiewiet (1981) on congressional voting patterns. Contrary to expectations of the pocketbook voting school, they found that voters who personally experienced unemployment were no more likely to cite it as an important national-level concern. What is more, their research gave support to the idea that macroeconomic conditions had a significant impact on voting choices. Later literature in this tradition moved closer towards accommodation with the pocketbook claims of self-interest but maintained the primacy of collective considerations over individual circumstances. One approach towards reconciliation of the literature is found in the work of Funk and GarcíaMonet (1997) where the idea of indirect self-interest was observed to have at least a secondary role to collective-level experiences in voting considerations. Another approach toward acknowledgment of the results of pocketbook voting literature is exemplified by the research of Markus (1988) who found that personal experiences themselves were able to carry weight without the need for some indirect intermediary, but that these experiences were generally less influential than macroeconomic conditions in predicting voting choices. An area of more fundamental debate among sociotropic voting scholars, however, is whether the collective-based judgments of voters occur at multiple levels or just on a single, national level. Scholars like Rogers (2014) have presented evidence of community-level decisions taking place alongside national level decisions. Such findings support the idea of a plethora of different collective determinations contributing to voting choices. At the same time, other scholars, such as Ragusa and Tarpey (2016), have continued to maintain the primacy of national perceptions. In their study of American National Election Study (ANES) responses from 1992 to 2008, it was found that the level of economic judgment that was influential in political choices depended on the functional responsibility of the officials up for election; national perceptions solely determined senatorial and presidential races because of this primacy of national conditions. A general criticism leveled at sociotropic voting is that the connection between economic perceptions and votes has been the result of the endogeny of voting choices in economic perceptions (Wlezien, Franklin, and Twiggs 1997). In other words, voters have already decided their partisan alignment before making considerations about national economic

Hours into Votes: Underemployment at the Ballot Box

conditions, and thus partisanship is mediating economic perceptions and not the other way around. The response of the sociotropic school to this can be found in Dickerson’s (2016) conclusions about the relationship between perceptions and partisanship – namely that the relationship is not constant. In years of economic distress, the economy becomes a salient point in people’s understanding of political performance and desirability; in years of relative prosperity, however, people assume economic performance as is convenient for their existing partisan alignment.

Reward and Punishment

Having looked at the two views of why economic voting happens, it follows that the two perspectives on how economic voting manifests should be considered next. The first and most direct approach to understanding the effects of economic voting is represented in the reward and punishment scholarship. The basic premise of this school is that voters who experience or perceive economic vulnerability will sanction the incumbent party for their poor economic management and reward them for prosperity (Kuklinski and West 1981; Singer 2013). An early example of this approach can be seen in the influential work of Kramer (1971). In his paper on the possibility of economic voting, Kramer proposed that there was an intrinsic benefit for congressional members of the incumbent party under positive circumstances and a corresponding oppositional advantage under negative economic circumstances. Fiorina’s (1978) research, which utilized Survey Research Center election studies to understand the role of retrospective economic voting, supplemented this early assertion. Through presenting evidence of a prosperitycontingent advantage of incumbent parties in presidential and congressional elections (although only present in presidential election years), Fiorina (1978) seemed to verify the intrinsic benefit suggested by Kramer (1971). This same fundamental approach can even be seen in the more contemporary research of Singer (2013), who showed in a cross-national study that the electorate usually sanctions incumbents who create risks for vulnerable workers, and those that have the benefit of overseeing times of greater opportunities for vulnerable workers tend to be awarded electoral advantage. Following the establishment of the basic theoretical framework of reward and punishment, scholars of this school narrowed down the influence of economics to examine how it affected incumbency in particular circumstances. For instance, Markus (1988) used ANES survey data to determine when incumbency was an asset. His research concluded that it was only helpful to be in the incumbent party when that party had presided over positive economic circumstances. A similar conclusion was arrived at in Brown and Woods’ (1991) model of the 1978 House elections; retrospective evaluations of economic performances were found to have a significant influence on the ability of the incumbent to capitalize on his or her position.

Discussion of rewards and punishment also lent themselves to research of how greater electoral context was important in considerations of economic circumstances. Kuklinski and West’s (1981) research of the 1978 U.S. House and Senate races found nuanced results. A significant relationship was seen between expected financial well-being and votes for the incumbent party in Senate races, but a similar influence could not be found in House races (although this also contained the interesting caveat that the unemployed remained generally loyal to the Democratic Party, just to differing degrees). These findings suggested that the less localized context of the Senate heightened the ability of voters to assign political responsibility to incumbent candidates. This view was generally endorsed throughout Lewis-Beck and Stegmaier’s (2000) comprehensive review of the literature on economic voting; they concluded their analysis of the literature with an endorsement of the recurring conclusions of reward and punishment and the importance of electoral context. A major criticism of this perspective is its inability to independently account for findings – like those of Kuklinski and West (1981) – that those affected by or concerned with specific economic issues tend to display remarkable partisan loyalty. Reward and punishment scholars can counter this problem somewhat due to the lack of a completely stable partisan composition of those influenced by particular concerns, which is precisely what Kuklinski and West (1981) do, but inevitably an ancillary explanation of economic voting behavior needs to supplement the theoretical understanding of this partisan loyalty. Thus, a significant weakness remains in this school of thought when it is taken on its own.

Issue Identification

The second and more indirect view of how economic voting manifests is that of issue identification. The core principle of this body of scholarship is that macroeconomic conditions are approached more in terms of policy preferences than a judgment of incumbent competency (Roemer 1994; Wright 2012). As a result, parties which have become identified with specific policies will always benefit from conditions that make people desire those policies. The foundations of this thought can be seen in the commentary of Goodman and Kramer (1975) where, despite generally maintaining the idea that voters were rewarding and punishing incumbents, they left open the possibility that some issues generally benefitted specific parties. It would take a while longer for this possibility to be explored further, but an early example was evident in Kiewiet’s (1981) inquiry into whether economic voting was policy- or incumbent-oriented. The resulting analysis on presidential and congressional elections between 1956 and 1978 revealed that voters personally affected by unemployment gave a slight boost to Democratic candidates and that there was a substantial advantage for the Democrats in years of high unemployment. This finding directly contradicted

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the view of an electorate who rewarded and punished incumbents of both parties based on economic performance. The idea of a consistent partisan advantage in the context of economic issues has since been extensively replicated within this school with similar results. In an analysis of presidential and gubernatorial elections between 1994 and 2010, Wright (2012) found that – other factors being equal – conditions of high unemployment consistently resulted in a Democratic advantage. In his explanation of these results, Wright (2012) referred back to the idea of unemployment as a partisan issue with the Democratic Party effectively presenting itself as the party concerned with unemployment. Gragstein (2005) contributed to the depth of this type of explanation by showing that the political impact of growth was mainly based on the ability of labor market participants to take advantage of said growth. Thus, the Democratic Party can represent its position on growth as geared towards the ability of the unemployed to take advantage of it. A final generalization of this logic was performed by Yong (2010), whose cross-national research showed that the issue salience of unemployment almost invariably favored center-left groups like the Democratic Party. As this research was taking place, scholars of the issue identification school also began constructing a broader theoretical account of economic voting. Roemer (1994), for example, argued that the environment in which parties become identified with issues is one in which voters do not have clear independent theories of how the economy works. Thus, parties are able to present strategic accounts of the economy and growth, which appeal to people in certain conditions such as unemployment. An empirical backing for this openness towards theories of the economy among voters was provided by Owens and Pedulla’s (2014) analysis of responses to the General Social Survey. Their findings were that people’s preference for distribution were malleable based on their personal economic perceptions and circumstances. Furthermore, Seeberg’s (2017) research on national election surveys from 17 countries showed that partisan issue ownership was stable across decades; taken together, these developments provide an account by which voters are open to whichever theory of the economy can address their concerns and they choose to support the party that has associated itself with the corresponding theory. An early and lasting criticism of this perspective, however, can be found in the work of Stigler (1973). Stigler (1973) questioned whether voters can determine the difference between the general economic preferences of political parties. The author pointed out, for example, that both parties represent themselves as caring about economic growth and rising wages; it would be politically unfeasible not to support these vague propositions, after all. The response of scholars in this school is embodied by Grafstein (2005) who argued voters accept a general commitment to growth as a given but are sensitive to who is able to make use of that growth. Despite this criticism, the issue identification school remains the most attractive tradition for the present research 10

on underemployment. While the pocketbook and sociotropic theories of voting are of great utility in understanding why underemployment may have an electoral influence, the sort of survey research that would be necessary to interrogate which path is taken by the relationship between underemployment and voting is not yet available. The reward and punishment school, on the other hand, may provide an auxiliary understanding of how underemployment is affecting voting, but its inability to independently explain the partisan advantages of unemployment calls into question its ability to perform a similar task for understanding underemployment.

Theory

The foundation of the issue identification school is its assertion that economic conditions are experienced as a partisan issue. Under this conception, it would be expected that underemployment would produce a Democratic partisan advantage like that provided by unemployment. What is more, this advantage would likely be the result of a shift of voters from the Republican Party. Likewise, a reward or punishment effect would not be expected, as the issue of underemployment would not be received as a criterion upon which to evaluate incumbents. During midterm elections, it would also be expected that there would be a lesser Democratic advantage. H1: If there is an increase in underemployment, then there will be an increase in the Democratic share of the vote. Scholars of the issue identification school have consistently matched perceptions of economic vulnerability and instability with support for the Democratic Party. The most recurring factor discussed in this literature has been unemployment – an index which occupies the same sphere of general employment prospects as underemployment. Given the proximity between the two variables, it was expected that underemployment will result in a Democratic advantage that mirrors that which has been found alongside unemployment. Such a result would gain underemployment a place in economic voting models alongside unemployment and generally expand our understanding of how economics factor in to vote choice. Furthermore, while the presence of some issue identification effects would not discount that there is a mechanism of reward and punishment, the strength of the relationship found here may show whether identification is a stronger or weaker component of vote choice. H2: If there is an increase in underemployment, then there will be a decrease in the Republican share of the vote. This second hypothesis was meant to supplement the results of the first hypothesis. While scholarship in the issue identification school has largely neglected to empirically model where the extra votes that form a Democratic advantage might come from, the theoretical literature on the subject suggests that there is a transition from the center-right to the center-left (as in a direct transfer from previously Republican voters to Democratic voters). It is precisely this effect that is expected

Hours into Votes: Underemployment at the Ballot Box

here, but it also seems plausible that the extra Democratic advantage might be derived from previously independent voters moving a shorter distance towards the Democratic Party. If the main effects of underemployment in these two regressions were opposite signs, then it would be an explanation of the view of exchanging votes between parties instead of outside of parties. H3: Underemployment will not have a significant main effect on the incumbent party vote share. The third hypothesis was meant to test the fundamental proposition of the scholarship proposing a model of reward and punishment about economic considerations. If voters responded to economic conditions by sanctioning the previously ruling party, then the main effect of underemployment would be expected to be negative and significant. Instead, it was expected here that the assertions of the issue identification school – that there would be no apparent influence of underemployment outside of a partisan context – would be affirmed. If voters are viewing underemployment as a policy rather than a valance issue, after all, they are not left much choice between parties. H4: In midterm elections, underemployment will provide a smaller Democratic advantage. This final hypothesis was meant to test the literature within the reward and punishment school that mentioned the possibility that voters approach elections differently based on electoral context. What is more, sociotropic critiques of pocketbook voting literature often suggested the difficulty of establishing clear links between economic issues and politics, especially on lower levels of government. These two perspectives synthesized with the view of underemployment as a valence issue led to the expectation that voting for a high profile elected official at the same time as a more local one would strengthen the politicization of underemployment. Conversely, not having such a clear partisan link (as in midterm elections) was expected to lessen the Democratic advantage.

Methods

Data in this study pertained to forty-nine states (excluding Alaska due to the lack of county-level results) on presidential and senatorial elections from 2004 to 2016. This data set was constructed from a variety of different sources. The three dependent variables – Democratic share of the vote, Republican share of the vote, and incumbent party share of the vote – were derived from Townhall Election Results (2004-2016), which aggregates election returns in a manner that was least labor-intensive to prepare for analysis. These three perspectives on the same elections were included to give a broad view of the influence of underemployment on voting. Elections in which there were either no candidates from one party or multiple candidates from one party were excluded from the analysis due to the difficulty of interpreting such electoral outcomes.

Regarding the independent variables, state underemployment (UNDER), as well as state and county unemployment (UNEM), were taken from the Bureau of Labor Statistics (2004-2016). Underemployment was here conceptualized as the U5 statistic of unemployment subtracted from the U6 statistic; this procedure left only the percentage of the labor force who were part-time for economic reasons. Such a conception only captures the narrowest definition of underemployment, but it is unfortunately the only officially produced indicator. Unemployment was included in this analysis to show that underemployment has a distinct influence on electoral outcomes that adds to existing models of economic voting. Racial variables were also included to control for demographic effects on economic and electoral outcomes. The data for racial variables were derived from the U.S. Census (2004-2016) estimates and initially included percentage of population on a state and county level for those who identified as the following: Black or African American (BLACK); American Indian or Alaska Native (NATIVE); Asian; and Native Hawaiian or other Pacific Islander. The incumbency status of candidates was included to control for traditional incumbency effects. In the regressions on partisan vote share, these variables were Democratic incumbent candidate (D_INC) and Republican incumbent (R_INC) while for the regressions on incumbent party share of the vote a generalized incumbent candidate (INC) variable was used. Finally, three variables were constructed for inclusion in the analysis of senatorial elections. The first of these was an indicator variable for midterm elections (MID) to capture the potential difference in voting behavior caused by accompanying presidential elections. The other two variables represented whether a Republican (RPRES) or a Democratic (DPRES) president was either presiding over a midterm election or running for another term.1 These variables accounted for the possibility that voters perceived economic issues differently based on higher office. This consideration arose from the reward and punishment literature previously discussed. Some prior research suggested that the presence of a president on the ballot may make it easier for voters to assign economic responsibility to a given party. Likewise, in a midterm election – without such a clear national actor – voters might have a more difficult time assigning responsibility to a given political party. Once the data were collected, the first step of the analysis was to produce county-level estimations of underemployment. The latter was conducted by adapting the method proposed by Gonzalez, Elena, and Hoza (1978). To begin, the method proscribed estimating the relationship between variables with known county and state-level values and the variable of interest which had only state-level values. To this end, a regression was estimated as UNDER = Constant + UNEM + BLACK + NATIVE2, providing coefficients which could be used to construct county-level estimates of underemployment. The results of this regression were as follows: UNDER = 1.136 +

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0.541 UNEM - 4.195 BLACK - 4.733 NATIVE with an R2 of .742. The coefficients indicate the change in underemployment for a one-unit change in the adjacent variable. The R2 indicates that 74.2% of the variability in underemployment was explained by the chosen variables – a fairly high amount that justified moving on to the next steps. The assumption then had to be made that the relationship between variables at a county level was similar to that at a state level. Moving forward with this assumption, the estimated state-level coefficients were multiplied by the county-level values of the respective explanatory variables and summed to provide predicted values of county-level underemployment. As a final step, the county estimations were weighted based on the actual level of underemployment over the predicted level of underemployment for each state from the earlier regression in order to account for the fact that the model only produced a national average of relationships. With county-level estimations of underemployment created, the analysis moved on to estimating the effects of underemployment on electoral outcomes. The first hypothesis was tested by including underemployment alongside control terms in a regression model of the Democratic Party share of the vote in presidential and congressional elections. The second hypothesis was tested by estimating a regression model of the Republican share of the vote on those same explanatory variables. The third hypothesis was evaluated by conducting a regression model on the incumbent party share of the vote to test whether there was a generalized mechanism of reward and punishment present in vote results. The nonpartisan indicator of incumbent candidates was used in these regression estimations to best model a general reward or punishment effect. Added to these models were also a number of interaction terms. These terms were included to account for the relationships that the explanatory variables may have with one another – for instance the way in which a changed electoral context, such as a midterm senatorial election, might have on the voting influence of employment status. The senatorial models also included the two aforementioned indicator variables for midterms and Democratic presidents to facilitate the evaluation of the fourth and fifth hypothesis. Finally, a series of diagnostic tests were run on the constructed datasets to make sure that there were no problems with multicollinearity, heteroskedasticity, autocorrelation, or model misspecification. The most important issue with multicollinearity among the variables was unsurprisingly between underemployment and unemployment; both conditions of employment result from the same macroeconomic problems, and one would expect them to rise and fall together. Independent models were estimated for both, and the resultant coefficients were compared to a combined model to ensure that their inclusion in the same equation was suitable. An application of White’s General Test also revealed some heteroskedasticity. The implication of this was that variance was inconstant, potentially resulting in significant terms being found insignificant. As almost all terms in all six 12

models ended up being significant, however, manipulating the model to eliminate this was deemed unnecessary. Positive autocorrelation was observed next, meaning that the error terms were correlated with one another across time. Unfortunately, this problem proved resilient to all attempts to remediate it. The risk with autocorrelation is that the standard errors and p-values can be incorrectly calculated. Sequentially adding elections to the dataset showed that the parameters had achieved relative constancy, instilling some confidence that the autocorrelation was not unduly affecting the analysis. Thus, for later interpretation, this problem was unresolved. Fortunately, there was no issue found with model misspecification.

Results

The results of the presidential vote regressions are shown in Table 1. Besides general findings of significance, Table 1. OLS Regressions on Presidential Vote Share Democrat

Republican

Incumbent

Constant

29.135*** 50.8

67.371*** 118.05

45.598*** 59.95

UNDER

-1.981*** -8.48

1.265*** 5.44

-4.005*** -12.93

UNEM

2.332*** 15.35

-1.637*** -10.83

2.725*** 13.54

D_INC

-2.224* -2.16

4.299*** 4.19

R_INC

6.592*** 6.02

-3.776*** -3.46

UNDER * D_INC

2.511*** 7.32

-2.094*** -6.14

UNDER * R_INC

1.243** 2.59

-0.492 -1.03

UNEM * D_INC

-1.52*** -7.58

0.973*** 4.88

UNEM * R_INC

-1.768*** -6.86

1.093*** 4.26

BLACK

0.275*** 27.6

-0.268*** -26.98

-0.063*** -4.82

INC

16.627*** 16.33

UNDER * INC

-2.835*** -7.23

UNEM * INC

-0.267 -1.10

0.148

0.124

0.083

13.603

13.536

18.042

240.517***

195.932***

189.043***

12446

Note: t-statistics are below estimated coefficients. *, **, and *** show significance at the 5%, 1%, and .1% levels.

Hours into Votes: Underemployment at the Ballot Box

the first immediate item of interest was the sign of the underemployment coefficient in the first two models. Contrary to the expectations of the first two hypotheses, underemployment displayed a Republican advantage and Democratic disadvantage in races where there was not an incumbent. Democratic presidents seemed to reverse this effect slightly, and Republican presidents appeared only to mitigate it somewhat. A possible explanation for these results is that the Republican Party presented a model of growth which those who face the prospect of unsatisfactory employment believe they can use to their advantage. Underemployed votersâ&#x20AC;&#x2122; preferences for redistributive policies, not being a position of total unemployment, are not emphasized as strongly and the focus is more on maintaining rather than gaining employment. Whenever voters were presented with incumbents, however, they paid less attention to the economic models presented by parties resulting in a lesser relationship between economic conditions and electoral outcomes. The general spirit of the first two hypotheses, however, was the expectation that there would be reciprocity between gains and losses between the two major parties. This expectation was met suggesting that underemployment acts in some capacity as a valence issue in presidential elections. The expectations of the third hypothesis found issues in the analysis; however, as underemployment had a clear main effect on incumbent party share of the vote. This confirmation of a punishment effect at first seemed at odds with the suggestion of a partisan nature of underemployment. Taken at the same time, though, these two results suggest that the assertions of both issue identification and reward and punishment schools of thought have merit. Moving on to the senatorial elections analyzed in Table 2, it can be immediately seen that the main effects of underemployment have remained consistent with results from the presidential election. This provided another general explanation of the logic behind the first two hypotheses. The interaction effects between underemployment and senator incumbency also provided evidence towards the treatment of underemployment as a partisan issue; regardless of the party of the incumbent, a Democratic disadvantage was predicted. A strange thing to note here, however, is that there is not a reciprocal exchange of votes predicted under a Republican incumbent like there is for a Democratic incumbent. It is possible this points to a punishment effect operating alongside a partisan advantage, with Republican incumbents not being able to capture disaffected potential Democrats when they have presided over underemployment. The third hypothesis found confirmation in the nonsignificant main term in the third regression, but at the same time, the interaction term between incumbent and underemployment was significant. Thus, voters did punish incumbents for conditions of underemployment, but they only did so when there was a candidate who could be assigned

responsibility for economic conditions. This contributed some understanding to the relationship between the two effects of punishment and identification seen in senatorial elections. Members of both parties faced punishment when Table 2. OLS Regressions on Senatorial Vote Share Democrat

Republican

Incumbent

Constant

36.263*** 47.16

59.882*** 78.08

56.097*** 64.21

UNDER

-1.927*** -6.81

2.156*** 7.63

-0.386 -1.21

UNEM

2.326*** 14.53

-2.446*** -15.32

-0.234 -1.26

BLACK

0.234*** 25.67

-0.201*** -22.11

-0.164*** -15.53

D_INC

22.055*** 25.05

-19.319*** -21.99

R_INC

-11.895*** -14.73

13.072*** 16.23

D_PRES

-5.962*** -14.79

5.796*** 14.42

R_PRES

-1.840*** -4.92

2.901*** 7.78

MID

9.308*** 10.22

-9.484*** -10.44

-3.045*** -3.63

UNDER * MID

2.227*** 8.51

-1.946*** -7.45

0.176 0.67

UNEM * MID

-1.433*** -9.49

1.444*** 9.58

0.324* 2.1

DPRES * MID

-14.811*** -19.49

12.991*** 17.14

UNDER * D_INC

-1.549*** -5.93

0.758** 2.91

UNDER * R_INC

-1.002*** -4.17

0.260 1.08

UNEM * D_INC

-0.353* -2.21

0.537*** 3.37

UNEM * R_INC

0.908*** 6.58

-0.587*** -4.26

INC

15.57*** 17.49

UNDER * INC

-0.886*** -3.22

UNEM * INC

-0.518*** -3.26

0.457

0.431

0.113

12.18

12.15

14.807

748.271***

674.06***

190.161***

13349

Note: t-statistics are below estimated coefficients. *, **, and *** show significance at the 5%, 1%, and .1% levels.

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their incumbent candidates presided over high levels of underemployment, but Republicans who held some valence advantage were punished somewhat less severely (a combined coefficient of -0.234 for Democrats against -0.075 for Republicans). The fourth expectation — that there would be a negative influence of midterm elections on Democratic results — was also shown to be incorrect. In fact, both Republican and Democratic candidates were predicted by their respective models to enjoy a small advantage from higher underemployment. Regarding the latter, there are a few things to consider. The first is that both parties achieving an advantage at the same time is not necessarily impossible, as it could represent economic conditions making third parties relatively less attractive. Another, perhaps more important point, is that the net effect of underemployment under these conditions is very small. A plausible explanation for this is that underemployment follows the trend of unemployment here to become relatively depoliticized, with the main focus of midterm elections being on the sitting president rather than policy issues.

CONCLUSION Despite its immense significance to everyday life, underemployment has thus far not found a place in models of economic voting. As a result, this paper looked into what were the effects of underemployment on electoral outcomes. Several regressions were estimated on presidential and senatorial elections from 2004 to 2016, testing whether underemployment resulted in a Democratic advantage, a Republican disadvantage, a punishment effect, or if underemployment had a stable influence across midterms and different electoral contexts. The first two hypotheses faced a dramatic reversal, with evidence of a Republic advantage and a Democratic disadvantage. The third hypothesis was also overturned, with both presidential and senatorial races showing some manner of a punishment effect. Taken together, it was seen that a complicatedf relationship existed between incumbents being held responsible for underemployment while Republicans held a general advantage over Democrats. Analysis of the fourth hypothesis showed both a Democratic and Republican advantage in midterms, pointing to a general depoliticization of the issue under those circumstances. Future research on the subject of underemployment may want to incorporate underemployment into a generalized economic voting model more explicitly. Additionally, one of the limitations of this research was the constrained time for which data were available for underemployment and betweencensus demographic estimations. This is something that will be naturally remedied assuming current data-collection projects continue. More data would have provided more options both for clarifying the influence of underemployment and address the problem with autocorrelation. 14

To conclude, underemployment has been shown to have a significant and nuanced influence on electoral results that is independent of unemployment. Economic voting models that neglect this potential employment status will thus fail to capture the whole image of peoples’ economic considerations. With the limitations of this research in mind, it is clear that future research on underemployment has the potential to expand and clarify further our understanding of the relationship between economic conditions and political choices. n

REFERENCES Brown, Robert D., and James A. Woods. 1991. “Toward a Model of Congressional Elections.” The Journal of Politics 53 (2): 454–73. Dickerson, Bradley. 2016. “Economic Perceptions, Presidential Approval, and Causality: The Moderating Role of the Economic Context.” American Politics Research 44 (6): 1037. Feldman, Stanley. 1982. “Economic Self-Interest and Political Behavior.” American Journal of Political Science 26 (3): 446–66. Feldman, Stanley. 1984. “Economic Self-Interest and the Vote: Evidence and Meaning.” Political Behavior 6 (3): 229–51. Fiorina, Morris P. 1978. “Economic Retrospective Voting in American National Elections: A Micro-Analysis.” American Journal of Political Science 22 (2): 426–43. Funk, Carolyn L., and Patricia A. García-Monet. 1997. “The Relationship between Personal and National Concerns in Public Perceptions about the Economy.” Political Research Quarterly 50 (2): 317–42. Gonzalez, Maria Elena, and Christine Hoza. 1978. “Small-area Estimation with Application to Unemployment and Housing Estimates.” Journal of the American Statistical Association 73 (361): 7-15. Goodman, Saul, and Gerald H. Kramer. 1975. “Comment on Arcelus and Meltzer, The Effect of Aggregate Economic Conditions on Congressional Elections.” American Political Science Review 69 (4): 1255–65. Grafstein, Robert. 2005. “The Impact of Employment Status on Voting Behavior.” The Journal of Politics 67 (3): 804-823. Kiewiet, D. Roderick. 1981. “Policy-Oriented Voting in Response to Economic Issues.” The American Political Science Review 75 (2): 448–59. Kinder, Donald R., and D. Roderick Kiewiet. 1979. “Economic Discontent and Political Behavior: The Role of Personal Grievances and Collective Economic Judgments in Congressional Voting.” American Journal of Political Science 23 (3): 495–527. Kinder, Donald R. 1981. “Sociotropic Politics: The American Case.” British Journal of Political Science 11 (2): 129–61. Kramer, Gerald H. 1971. “Short-Term Fluctuations in U.S. Voting Behavior, 1896–1964.” American Political Science Review 65 (01): 131–43. Kuklinski, James H., and Darrell M. West. 1981. “Economic Expectations and Voting Behavior in United States House and Senate Elections.” The American Political Science Review 75 (2): 436–47.

Hours into Votes: Underemployment at the Ballot Box Lau, Richard R., and Caroline Heldman. 2009. “Self-Interest, Symbolic Attitudes, and Support for Public Policy: A Multilevel Analysis.” Political Psychology 30 (4): 513-526. Lewis-Beck, Michael S. 1985. “Pocketbook Voting in U.S. National Election Studies: Fact or Artifact?” American Journal of Political Science 29 (2): 348-66. Lewis-Beck, Michael S., and Mary Stegmaier. 2000. “Economic Determinants of Electoral Outcomes.” Annual Review of Political Science 3 (1): 183-213. Markus, Gregory B. 1988. “The Impact of Personal and National Economic Conditions on the Presidential Vote: A Pooled CrossSectional Analysis.” American Journal of Political Science 32 (1): 137–54.

Yong, Hyeok Kwon. 2010. “Unemployment, Partisan Issue Ownership, and Vote Switching: Evidence from South Korea.” Party Politics 16 (4): 497–521.

NOTES 1. This approach was chosen over a single dichotomous partisan incumbent variable which would have treated elections dominated by an incumbent president identically to open presidential elections like 2016. 2. Other racial variables were either not significant or found to not add enough explanatory power to the model to be worth including.

Mutz, Diana C. 1993. “Direct and Indirect Routes to Politicizing Personal Experience.” Public Opinion Quarterly 57 (4): 483. Owens, Lindsay A., and David S. Pedulla. 2014. “Material Welfare and Changing Political Preferences: The Case of Support for Redistributive Social Policies.” Social Forces 92 (3): 1087–1113. Petrow, Gregory A, and Timothy Vercellotti. 2016. “How Our Life Experiences Affect Our Politics: The Roles of Vested Interest and Affect in Shaping Policy Preferences.” American Review of Politics 32 (3): 1–29. Ragusa, Jordan M., and Matthew Tarpey. 2016. “The Geographies of Economic Voting in Presidential and Congressional Elections.” Political Science Quarterly (Wiley-Blackwell) 131 (1): 101-120. Roemer, John E. 1994. “The Strategic Role of Party Ideology When Voters Are Uncertain About How the Economy Works.” The American Political Science Review 88 (2): 327–35. Rogers, Jonathan. 2014. “A Communotropic Theory of Economic Voting.” Electoral Studies 36 (4): 107–16. Seeberg, Henrik Bech. 2017. “How Stable Is Political Parties’ Issue Ownership? A Cross-Time, Cross-National Analysis.” Political Studies 65 (2): 475–92. Sears, David O., and Richard R. Lau. 1983. “Inducing Apparently Self-interested Political Preferences” American Journal of Political Science 27 (1):223-52. Singer, Matthew M. 2013. “What Goes around Comes around: Perceived Vulnerable Employment and Economic Voting in Developing Countries.” European Journal of Political Research 52 (2): 143–63. Stigler, George J. 1973. “General Economic Conditions and National Elections.” American Economic Review 63 (2): 160–67. Townhall Media. 2004-2016. Townhall Election Results. https:// townhall.com/election/. U.S. Bureau of Labor Statistics. 2004-2016. Local Area Unemployment Statistics. https://www.bls.gov/lau/. U.S. Census Bureau. 2004-2016. Selected Individual Characteristics, American Community Survey 5-year estimates. https://www.census. gov/programs-surveys/acs. Wlezien, Christopher, Mark Franklin, Daniel Twiggs. 1997. “Economic Perceptions and Vote Choice: Disentangling the Endogeneity.” Political Behavior 19 (1): 1-17. Wright, John R. 2012. “Unemployment and the Democratic Electoral Advantage.” The American Political Science Review 106 (4): 685–702. © Pi Sigma Alpha 2019

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Polarization and Party Cohesion in Campaign Messaging: Do Female Republican Senate Candidates Rely More Heavily on Party Cohesion Messaging in Campaign Advertisements? Allison R. Cyrus, University of Tennessee, Chattanooga Despite significant gains for women’s representation in Congress resulting from the 2018 midterm elections, the Republican Party remains significantly disproportionate to the Democratic Party in descriptive representation of women, particularly in the U. S. Senate. Many scholars have pointed to the phenomenon of asymmetric partisan polarization within the Republican ranks as a key factor in preventing gender parity in legislative representation. Moreover, additional research within this vein demonstrates that gendered stereotypes create significant barriers for female Republican candidates, both electorally and in the context of internal partisan hierarchy. This research seeks to provide a greater understanding of the intersection of gender trait stereotypes, partisanship, and polarization through an examination of campaign messaging related to internal party alignment or cohesion. Is there evidence that female Republican candidates utilize party cohesion messaging in their campaign advertisements to a greater extent than female candidates within the Democratic Party or their male co-partisans? A content analysis of multi-media digital campaign advertisements available through a repository on YouTube of both male and female United States Senate candidates of the Republican Party and the Democratic Party is conducted for evidence of party cohesion messaging. This study finds that, given the conditions of asymmetric partisan polarization within the Republican Party, female Republican candidates are more compelled to demonstrate their support and alignment with the policy agendas of the elite cleavages within the Republican Party.

INTRODUCTION he 2018 midterm election resulted in significant gains for women in legislative and gubernatorial offices. In the U.S. Senate, there are now twentyfive female senators: seventeen female Democratic senators and eight female Republican senators (Center for American Women and Politics 2018). While the House of Representatives and gubernatorial seats across the U.S. also achieved significant shifts in gender diversity, one glaring disparity remains. The vast majority of the women elected to office, across all governmental capacities, were Democratic candidates (Center for American Women and Politics 2018). Women remain grossly under-represented in the Republican ranks of government within the U.S. Much of the news media hailed the 2018 midterm election as a landmark gain for gender descriptive representation, yet the number of female Republican senators only increased by one from the 2016 election season (Todd, Murray, and Dann 2018). This troubling reality has not been a recent realization. Political

Science scholars have researched the phenomena of gendered representation (or lack thereof ) within the Republican Party for several years, formulating several explanatory frameworks for the obstacles facing Republican women in legislative office (Schreiber 2018). Asymmetric partisan polarization among Republicans is a critical component of the prevailing theories. The problem of asymmetric partisan polarization has been defined as the movement of Democratic and Republican leaders toward ideological polar extremes, with considerably more rightward conservative movement by Republicans (Schreiber 2018). Within the Republican Party, asymmetric partisan polarization has disenfranchised the moderate members of the party’s base (Hall and Thompson 2018). The hyper-conservative Tea Party Republicans, who came to prominence in the party’s ranks in 2010, helped exponentially in achieving majority status for Republicans in the House and Senate, as well as securing President Trump’s election in 2016 (Swers 2018, 203). Their platform embraces staunch support of the party and

Polarization and Party Cohesion in Campaign Messaging / Female Republican Senate Candidates

presidential agenda, and moderate ideology is largely rejected (Mann and Ornstein 2016). Indeed, Republican legislators who espouse moderate ideology or policy stances are termed “RINO’s”, or Republican in Name Only (Schwartz 2018). Surveys of U.S. congressional voting behavior have unequivocally demonstrated that Republican women, particularly those in the Senate, tend to vote “markedly less conservative than their male counterparts” (Swers 2018, 206). Moreover, studies have consistently shown that gender stereotypes of women carry different consequences for female candidates contingent on their partisan affiliation (Dolan 2014). “Republican women candidates tend to have a harder time winning party primaries (Lawless and Pearson 2008), and ideological stereotypes can hurt Republican women candidates with Republican voters but increase their appeal to Democrats and Independents…” (Dolan 2014, 42). When this observable tendency toward centrism is combined with the effects of gender and ideological stereotyping, conservative Republican voters tend to assess female Republican candidates as being less committed to conservativism (Lawless 2004). According to voter choice and behavioral models, voters will tend to choose the candidate perceived as most viable, even when they ideologically or otherwise identify with a different candidate (Peterson 2017; Philpot and Walton 2007). For staunchly conservative Tea Party Republicans, candidate viability effectively translates to cohesion to conservativism and the party’s policy agenda (Lawless 2004). The result of these interacting perceptions and phenomena is that “…today’s Republican women need to be strong conservatives who can appeal to an increasingly conservative primary electorate…” (Swers 2018, 203). Given the above observations and findings, it seems reasonable to make an inquiry as to what impact these stereotypical evaluations have on the messaging of Republican women’s multi-media, digital campaign advertising. Do female Republican candidates rely more heavily on party cohesion messaging compared to female Democratic candidates? Moreover, can similar differences in party cohesion messaging utilization be found between female Republican candidates and their male co-partisans? This content analysis seeks to address such a query, as it measures party cohesion messaging differences between male and female U.S. Senate candidates of both major parties. Evaluating the comparisons and contrasts of campaign messaging between both levels of partisanship and gender will demonstrate whether female Republican U.S. Senate candidates utilize party cohesion messaging in their multi-media digital campaign advertisements at a higher rate due to solely partisan differences or due to gendered partisan differences.

Literature Review

Dolan’s (2014) book, When Does Gender Matter, presents an in-depth analysis of gender stereotypes in relation to attitudes toward and support for female candidates, as well as 17

the intersections of gender stereotypes and voter behavior and perceptions. Because female candidates are aware of gendered stereotypes and their impact on candidates, “women candidates can make strategic choices about whether to campaign in line with stereotypes by focusing on ‘female’ issues, or they can try to counter stereotypes by including more ‘male’ issues in their presentations” (Dolan 2014, 47; 63). In order to evaluate the degree to which campaigning within the framework of gender stereotypes occurs, Dolan (2014) analyzed television campaign advertisements and digital media promulgated by candidates. The author notes that, much in the same way the voters use partisan cues to make vote decisions in the absence of political information, similar phenomena have been exhibited among voters relating to the intersection of candidates, policy information, and gender. Essentially, if a candidate’s campaign advertisements do not convey policy stances or messaging regarding relevant areas of policy, voters may utilize the candidate’s gender as a means of assessing policy stances or competency (Dolan 2014). Cassese and Holman (2018) examine the interaction of gender stereotyping, partisanship, and campaign messaging. While voluminous research exists regarding negative campaign advertisements, Cassese and Holman (2018) evaluated the impact and efficacy (or lack thereof ) of attack campaigning when stereotypes relating to partisanship and gender are factors. The study concludes that, among the American electorate, there is a discernable association of gendered trait conceptions with partisan identification and correlating issue areas. According to previous literature used to construct their study, “Americans associate competence on feminine policy issues and traits with the Democratic Party and masculine policy issues and traits with the Republican Party” (Cassese and Holman 2018, 790). Strikingly, Cassese and Holman’s (2018) study also renders evidence that female candidates are not benefitted by displaying proficiency in perceived masculine policy traits, particularly if they fail to show proficiency in the stereotypical feminine policy traits. Ultimately, it is concluded that while “female candidates are more harmed by attacks that emphasize stereotypically feminine traits” (Cassese and Holman 2018, 803-804), gender leads vote choice and evaluations of candidates, contrary to the hypothesis that vote choice and candidate evaluations occur at the junction of gender and partisanship. This confirms the findings of studies such as Dolan’s (2014) and is informative to understanding how candidate evaluations and vote choice are made at the intersection of gender and party identification for Republican women (Cassese and Holman 2018). At the forefront of scholarship regarding women in elected office, Hayes and Lawless (2016) evaluate the impact of the current state of polarization within American politics on female candidates running for office. They assert that “As the parties have grown further apart…they have also become more internally cohesive…in a polarized system, party exerts

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stronger influence, leaving fewer opportunities for other factors to shape a campaign’s content” (Hayes and Lawless 2016, 19). Since the Republican Party is asymmetrically polarized (leaning further ideologically right or conservative than the Democrats lean ideologically left or liberal), and partisan polarization has increased internal cohesion within the parties, it stands to reason that—by virtue of being the most polarized—the Republican Party should also be at least slightly more internally cohesive than their Democratic counterpart. If female candidates within the Republican Party must overcome gendered stereotypes in order to convey themselves as competent in the masculine-stereotyped policy traits that their party is internally aligned on, are they more motivated to incorporate party cohesion messaging into their campaign advertising? Additional support for the idea that polarization, particularly on the Republican side of the aisle, has the impact of increasing partisan candidate assessments (ignoring or rejecting other factors outside of partisanship) is garnered through the dissemination of survey data from 2010 through 2014 (Hayes and Lawless 2016). Theodoridis’s (2017) findings regarding partisanship, implicit identity and political understanding are mirrored closely in Hayes’s and Lawless’s findings. “We find that voter’s attitudes have little to do with whether candidates are men or women and everything to do with whether they are Republican or Democrat” (Hayes and Lawless 2016, 93). Additional studies conducted by Dolan and others (Sanbonmatsu and Dolan 2009; Dolan 2010), acknowledge this prevailing reliance on partisanship within the electorate, offering further exploration of the unique problems posed to Republican female candidates. Dolan (2010) points to research providing evidence that female Republican candidates have more difficulty gaining the vote share within their party than their female Democratic counterparts. She goes on to opine that, “…this is because issue and trait stereotypes of women and of Democrats are generally consistent with each other, while stereotypes of women and of Republicans are more at odds with each other” (Dolan 2010, 72). The internal structure, political culture, and ideological platform of the Republican Party pose barriers to the growth of women’s representation (Wineinger 2018). According to Wineinger’s (2018) study, the internal culture and dynamic of the Republican Party from the Reagan era to the present has been shaped by conservative ideology. “[The] conservative ideology that unites the Republican Party is best described as…an ideology that unites the values of social conservativism, laissez-faire capitalism, and a strong national defense” (Wineinger 2018, 27). Republican policy priorities have consistently remained centered on national security, entrepreneurial and business-focused economic policies, and traditional conservative social values—the bulk of which happen to be “masculine” policy areas (Wineinger 2018, 2728). Moreover, a general rejection of identity politics within 18

the Republican Party’s internal culture is also posited to be a limiting factor in women’s representation, as candidate recruitment and support networks for female candidates (i.e., Emily’s List, etc.) receive considerably less support from party leadership than those of the Democratic Party (Wineinger 2018, 27; Fox and Lawless 2004). Top-down leadership structures within the Republican Party are also impactful. Adherence to party leadership has been a core cultural norm of the Republican Party, yet the recent influence of the Tea Party within the Republican ranks has shifted this aspect of the internal culture (Wineinger 2018). The Tea Party movement within the Republican Party has altered the cultural norms on confrontational politics, particularly relating to internal party leadership. Essentially, Tea Party Republicans have made the internal cultural norm of the party to demand that leaders hold and promote extremely conservative positions; thus, adherence to leadership is expected unless leadership fails to be conservative enough (Wineinger 2018). Given these structural, cultural, and internal political developments, the implications for Republican women’s representative growth are vastly negative. Numerous studies have demonstrated that female Republican candidates are perceived as less conservative and more moderate than male Republican candidates (Och and Shames 2018; Swers 2018; Wineinger 2018). The emphasis on predominantly masculine gendered policies and conservativism creates an inherent disadvantage for female candidates, “…as they must work to credential themselves as adequately conservative members of their party” (Wineinger 2018, 30). Existing research and scholarship in the study of gender, partisanship, and effective campaign messaging contains considerable evidence demonstrating that female Republican U.S. Senate candidates rely more heavily than their Democratic counterparts on party cohesion messaging in campaign advertisements. It seems reasonable that if female Republican candidates want to be successful in their electoral bids, they will be interested in gaining the largest possible vote share of their own partisan base. According to the prior research, this seems to be most effectively done by transcending all other evaluating factors with a strong message of party cohesion (Swers 2018).

Methods Advertisement Sample

To content analyze multi-media digital campaign advertisements for party cohesion messaging, two hundred campaign advertisements were compiled, including one hundred campaign advertisements from each of the male and female candidate sample sets, from the 2018 U.S. midterm election period. Campaign advertisements were viewed spanning a period of approximately four weeks, which included time prior to and after the November 6, 2018, election. Specifically, these advertisements were originally

Polarization and Party Cohesion in Campaign Messaging / Female Republican Senate Candidates

released between August 2018 and November 2018, and were viewed mostly through the “U.S. Political Adverts” page on YouTube (https://bit.ly/2XbW7K0), although a few were only available through candidates’ YouTube channels. The YouTube page (U.S. Political Adverts) is a repository of campaign advertisements from 2018 U.S. Senate, House, and state gubernatorial candidates, as well as some more recent presidential primary candidate campaign advertisements. Many of the uploaded advertisements were aired on television in their respective media markets, while some were available exclusively online (i.e., from YouTube candidate pages, webpages, and other online media sources). Scholarly analysis on campaign advertising from the 2018 midterm election cycle posits that a variety of media sources were utilized by candidates across congressional and state electoral races. Thus, it is reasonable to be able to expect digital, online, and televised campaign advertising formats to disseminate messaging in a fairly consistent manner, as the electorate now views political campaigning across a broad mix of media sources (Fowler, Franz, and Ridout 2018). The multi-media digital campaign advertisements analyzed came from a total of 32 U.S. Senate candidates from across the country, comprised of sixteen female candidates and sixteen male candidates. Within each of the female and male candidate samples, eight of the candidates were Republican, and eight of the candidates were Democrats. Candidates were selected based on 2018 Senate midterm race watch lists from Center for American Women and Politics (2018) and Ballotpedia (2018). The selection of candidates was based primarily on being contenders in their state’s general U.S. Senate election for the 2018 midterm election cycle; however, the availability of digital advertisements was also considered. The candidates that were ultimately selected were those who had campaign advertisements accessible through YouTube’s “U.S. Political Adverts” page or their own candidate YouTube channels.1 The candidate pool contained a mixture of incumbents, challengers, and open-seat contenders. Advertisements were selected from the YouTube campaign advertisement repository (“U.S. Political Adverts”) in order to create sample sets for each candidate from the male and female sets (as previously mentioned, some had to be pulled from candidates’ YouTube channels in order to have full sample sets). Generally, ten advertisements out of the available advertisements for each candidate were selected, although some candidates had fewer than ten advertisements available. Each advertisement in the sample set was assigned a numeric identifier (1-100 for each of the male/female sets). A random number generator was utilized to determine the order of viewing for each set of the campaign advertisements from the repository. This was done to keep the viewing cycle as randomized as possible while ensuring that out of each set of one hundred advertisements (male and female sets), approximately half were from Democratic candidates and half were from Republican candidates.

Advertisement Coding

Based on the previously discussed literature, a coding sheet with sixteen variables was developed to content analyze each ad. (See the codebook in the Appendix). First, each ad was coded for Candidate Identity. The candidates were deidentified by assigning their respective identities numeric codes ranging from 1 to 32. Following this, ads were coded for candidate Partisan Affiliation, coded as a 1 for Democratic and a 2 for Republican. Incumbency Status was then recorded, with candidates running as challengers denoted with code 1, incumbents were coded as 2, and open-seat contenders were coded as 3. This information was verified through the information provided by the Center for American Women and Politics (2018) and Ballotpedia (2018). Lastly, each ad was coded for campaign content variables, including: Focus of Advertisement (candidate, opponent, or party), Party Support Messaging, Party Opposition Messaging, three subsets of Republican Policy/Issue Messaging (National Security, Economy, and Social Issues), three subsets of Democratic Policy/Issue Messaging (Education/Healthcare, Economy, and Social Issues), Support of President Trump’s Agenda, Ideology Messaging, Bipartisanship Messaging, and Qualification Messaging. The Focus of Advertisement was coded for attention on the candidate (herself/himself ) (1), opponent (2), and party (candidate’s own or opponent’s) (3). Party Support Messaging, which was defined as any explicit mention or imagery relating to the candidate’s party, was coded according to strong Democrat (1), Democrat (2), strong Republican (3), Republican (4), and no explicit mention of party support (5). The code construction for Party Opposition Messaging was similar to that of Party Support Messaging: (1) Strong antiDemocrat, (2) anti-Democrat (3) strong anti-Republican, (4) anti-Republican and no explicit mention or imagery related to the opponent’s party (5).

Republican and Democratic Policy Messaging Variables and Coding

Both Republican and Democratic partisan issue sets were coded for all candidates (male and female) to measure any occurrence of cross-partisan campaign messaging. Examples of cross-partisan campaign messaging—although not a frequent occurrence among the advertisements surveyed—would include Democrat Joe Manchin (WV) adamantly supporting 2nd Amendment gun rights, or Republican Dean Heller (NV) noting his work to pass the Violence Against Women Act, which his party opposed. The Republican and Democratic policy messaging areas and subsets were selected through a synthesis of existing scholarship and sample previewing (Deckman 2018; Democratic National Committee 2016; Fiorina 2017; Republican National Committee 2016; Wineinger 2018). Party cohesion is defined by the internal ideological cohesiveness of the partisan platform (Fiorina 2017). Within the context of partisan polarization, the internal ideological cohesion of political parties becomes more ideologically homogenous,

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so that there is no real overlap between the ideological and policy stances of the political parties (Fiorina 2017). Because the Republican Party is asymmetrically polarized toward conservative ideology, its internal cohesion is typified by conservative values and policies. Moreover, because of the structural and internal cultural norms of the Republican Party, party ideology and leadership are to be adhered to and promoted by candidates in order to be aligned with the party platform (Wineinger 2018). With a conservative, Republican president in office, party leadership is largely focused on President Trump. Trump has set a priority agenda centered on national security, immigration, tax cuts to help businesses boost employment and economic growth, conservative social policies, and conservative judiciary appointments to support pro-life, pro-religious freedom, and pro-family values in constitutional jurisprudence (Deckman 2018; Republican National Committee, 2016; Wineinger 2018;). Given that the Republican Party’s internal political culture and guiding ideology is centered on party leadership (top-down structuring) and conservativism, it is reasonable to deem policy areas covering these issues (along with some closely correlated ones) as policies and/or issue areas that demonstrate adherence to the party’s ideological and policy commitments and, thus, party cohesion. The Democratic Party, conversely, is structured around group and identity politics (Wineinger 2018). Essentially, the Democratic platform represents policy commitments based on the group interests that the party has coalesced around. While partisan polarization for the Democratic Party has involved some movement toward a more overall liberal ideology in the party’s platform, the Democrats have not moved as far to the liberal pole and the Republicans have to the conservative pole (Fiorina 2017; Wineinger 2018). Still, it is an element of the party’s internal policy and ideological cohesion. The policy issue areas represented in the three messaging areas are the central policies (some representing a broader umbrella of related policies) related to the dominant group interests and broader liberal ideology outlined in the party’s 2016 platform (Democratic Platform Committee 2016). It seems reasonable, then, to correlate these policy points and issue areas to demonstrating internal party cohesion within the Democratic Party. Sample previewing was conducted by viewing small sample sets of advertisements composed of two to three multi-media digital campaign advertisements from each of the candidates in the sample (drawn from the YouTube repository). Most of the campaign advertisements utilized the policy messaging that correlated to the elements of partisan cohesion discussed throughout the existing body of literature. Those that did not were generally attack advertisements focused on a specific statement or incident involving the opponent. The bulk of these attacks were too unique to the specific race to be reasonably correlated to party cohesion and thus were not incorporated into the coding scheme. The element of party cohesion relating to asserting a candidate’s 20

commitment to the party’s ideology through highlighting their opponent’s deficiency (in commitment or ideology) is, however, incorporated into coding for Focus of Advertisement, Party Opposition, and Ideology Messaging. To establish party cohesion messaging, the three (three each, for a total of six) partisan messaging variables were designed to relate policy areas to Republican or Democratic policy traits or stereotypes. For the Republican Party, the groupings were Republican National Security Issues, Republican Economic Issues, and Republican Social Issues. The sub-sets under Republican National Security were immigration and/or border wall related policy, security and military, and gun rights. A code of 1 would represent immigration and/or border wall policies, code 2 represented gun rights, and code 3 represented security and military policies. Combinations of these issues, representing instances of when a candidate’s advertisement mentioned a combination of two or more of these policy areas (i.e., immigration and military or gun rights and national security), were represented with codes 4, 5, 6, and 7. With all sets of Republican and Democratic trait policies, code 8 equated “none of the above.” For the subset of Republican Economic Issues, policies relating to taxes or tax cuts were coded as 1, entitlement reform policies were coded as 2, and healthcare reform was coded as 3. As with the National Security Issues subsets, codes 4, 5, 6, and 7 denoted combinations of codes 1 through 3. The final Republican trait policy category, Republican Social Issues, was comprised of a similarly structured subset as those for National Security and Economic Issues. Code 1 represented pro-life policies, code 2 represented religious freedom, and code 3 represented family values. Again, codes 4, 5, 6, and 7 related to combinations of these policy traits. The three Democratic policy trait categories were constructed in much the same way that the Republican sets were. Within the first subset, Democratic Education and Healthcare Issues, the first policy area was Education and STEM (Science, Technology, Engineering, and Mathematics) Improvements, and was coded as 1. Next, Healthcare Expansion policies received a code 2. Opioid Crisis policies were coded as 3. Codes 4, 5, 6, and 7 represented combinations of the policies described in codes 1 through 3. The second Democratic policy set was Democratic Economic Issues. This subset included policy areas labeled Fiscal Transparency, Entitlements and Social Welfare, and Living and/ or Equitable Wage, coded 1, 2, and 3, respectively. As previously evidenced, codes 4, 5, 6, and 7 related to combinations of policy codes 1 through 3. Lastly, Democratic Social Issues contained three policy trait subsets, labeled Pro-Choice policies, Racial, Gender, and/or Lesbian, Gay, Bisexual, Transgender, Queer (LGBTQ) Equality issues, and Sexual Harassment and/or MeToo Movement policies and/or issues. Pro-Choice was assigned code 1. Racial, Gender, and/or LGBTQ Equality was assigned code 2. Finally, Sexual Harassment and/or Me-Too policies and/ or issues were labeled as code 3. Combinations, as in all cases, were represented by codes 4, 5, 6, and 7.

Polarization and Party Cohesion in Campaign Messaging / Female Republican Senate Candidates

Non-Policy Messaging Variables and Coding

The last four variables coded for were labeled Support of President Trump, Ideology Messaging, Bipartisanship Messaging, and Qualification Messaging. Each of these variable coding schemes utilized scales. Support of President Trump was coded on a scale of 1 through 4, with strong supporter (1), moderate supporter (2), weak supporter (3), and non-supporter (4), and no explicit mention or imagery in support or dissent of President Trump or his policy agenda (5). Ideology Messaging was coded on a scale representing the ideology espoused, if any, by the advertisement. For this reason, the scale used in this instance related to ideology was not the seven-point Likert scale. Instead, ideology was coded on a 1 to 4 scale, as conservative values messaging (1), liberal values messaging (2), moderate values messaging and code (3) and no mention or messaging related to ideology (4). Bipartisanship Messaging had three potential codes: the candidate expresses a willingness to engage in bipartisanship (1); the candidate expressed unwillingness to engage in bipartisanship (2), and represented no mention or messaging related to bipartisanship (3). Qualification Messaging also contained three potential codes: the candidate mentioning career qualification (generally relating to the private sector) (1); the candidate mentioning their political career and/or partisan qualification (2), and no mention of the candidate’s qualifications for political office (3).

Coding Reliability and Measurement

Utilizing a mostly random selection of advertisements and having a fairly even spread of partisanship among the candidates served to provide external validity to the content analysis. A second coder coded twenty-five percent of the sample to ensure the reliability of the coding scheme. The Cohen’s Kappa for overall inter-coder reliability for the sample is .831, which is well over acceptable reliability thresholds.

Sixteen variables in total were coded, with a low-end reliability score of .639 and a high-end score of 1.00.2 Once coded for each of the sixteen variables and variable subsets in the codebook, the data were analyzed for each variable’s code frequencies, in order to disseminate which candidates utilized messaging related to party cohesion more often in their campaign advertisements. Based on the availability of the advertisements and the restriction that the candidates must be running for U.S. Senate, it was not possible to compile an even number of advertisements by party, as was done in the candidate selection (eight Democrats and eight Republicans for each of the male/female sample sets, thirty-two total). Candidates such as Deb Fischer and Susan Hutchison (both Republican), as well as Sherrod Brown and Sheldon Whitehouse (both Democrats), each had only one, two, or three accessible campaign advertisements through the U.S. Political Advertisements YouTube repository or the candidate’s own YouTube channels and/or campaign websites. Ultimately, forty-five of the advertisements were from female Republican candidates, and fifty-two were from male Republican candidates. The Democratic candidate sample consisted of fifty-five advertisements from female candidates and forty-eight advertisements from male candidates. Despite this difference, it would still be reasonable, based on the frequency distribution of specific variables, to ascertain whether Republican women rely more heavily on party cohesion messaging in their campaign advertisements.

Findings Party Support, Party Opposition, and Focus of Advertisement Figures 1A-1C and 1D-1F, respectively, display the frequency results for the Party Support and Party Opposition variable sets. Interestingly, none of the advertisements for Democratic male candidates rendered Party Support Messaging

Figure 1A. Party Support Messaging Republican Women

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Figure 1B. Party Support Messaging Republican Men

Figure 1C. Party Support Messaging Democratic Women

codes. On the whole, both Democratic males and females tended to focus on messaging relating to their independent partisan voting and legislative endorsement behavior. This, of course, could merit a completely separate study, which cannot be conducted here. As the Figures illustrate, Democratic women did utilize partisan support messaging, but only moderately (no advertisements received a “Strong Democratic” party support code) and dramatically less than their Republican male and female counterparts. Campaign advertisements utilizing party support messaging among Democratic female candidates comprised only 5.5% of their advertisements (see Figure 1C). Although “no mention of candidate’s party” (code 5) received the greatest distribution (see Figures 1A-1C) for most of the sample groups, a closer look reveals a great deal more. For the Party Support variable, recall that code 3 denoted Strong Republican. Strong Republican received the highest frequency of the four codes relating to specific partisan support 22

for both Republican men and women. However, the difference in the frequencies for Party Support Messaging (for Strong Republican and Republican variables) between Republican men and women are striking. Among Republican women, 31.1% of advertisements displayed Strong Republican Party support messaging, and 20% were coded for Republican Party support messaging (moderate explicit party support). Fifty percent of all the campaign advertisements for Republican women represented explicit Party Support Messaging (see Figure 1A). In contrast, only 7.7% of campaign advertisements from Republican male candidates coded as containing Strong Republican Party Support Messaging, and only 3.8% were coded for Republican Party support messaging. The aggregate total for Republican male candidates’ advertisements conveying explicit Party Support Messaging reflected 11.5% of the male Republican sample—nearly forty percent less than female Republican candidates (see Figure 1B).

Polarization and Party Cohesion in Campaign Messaging / Female Republican Senate Candidates

Figure 1D. Party Opposition Messaging Republican Women

Figure 1E. Party Opposition Messaging Republican Men

Figure 1F. Party Opposition Messaging Democratic Women

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Measurements of the Party Opposition Messaging variables also reveal dramatic differences between female candidates of both parties and between male and female Republican candidates. Again, Democratic female candidates are the least engaged in the utilization of Party Opposition Messaging, with only 1.8% of campaign advertisements classified as Strong Anti-Republican and 5.5% of campaign advertisements coded as Anti-Republican (see Figure 1F). For the male and female Republican candidate groups, the Republican males demonstrate a higher rate of Party Opposition Messaging in their campaign advertisements. Within the sample of male Republican candidates, 19.2% of advertisements displayed Strong Anti-Democrat party opposition messaging, and 13.5% were coded for containing Anti-Democrat party opposition messaging (see figure 1E). For the Republican female candidates, 11.1% of campaign advertisements conveyed Strong Anti-Democrat partisan opposition, and 6.7% received Anti-Democrat party opposition messaging codes (see Figure 1D). These variances could reasonably be attributed to female Republican candidates prioritizing positive party cohesion messaging to overcome the valence gap of gendered stereotypes and trait perceptions in order to gain the vote share within their conservative Republican base (Wineinger 2018). The results of the Focus of Advertisement variable could reasonably be viewed in correlation with the Party Opposition variable findings. Similar to the difference in partisan opposition messaging between Republican male candidates and Republican female candidates, over half of the advertisements (67.3%) in the Republican male group were found to be opponent focused, and 32.7% were candidate focused. Among the advertisements from female Republican candidates, 62.2% of all advertisements received candidate focused coding, and 24.4% were opponent focused. The remaining 13.3% were coded as party platform focused. It should be noted that, apart from one Democratic male candidateâ&#x20AC;&#x2122;s advertisement, no other

group displayed any frequencies for the party platform focus for the Focus of Advertisement variable. The code frequencies for Democratic male candidates and Democratic female candidates were (as with most other variables between the two groups) highly similar. For Democratic females, 74.5% of all advertisements were candidate focused), and 25.5% were opponent focused. Within the Democratic male candidate group, 75% of advertisements were candidate focused, 22.9% were opponent focused, and 2.1% were coded as party platform focused. Again, these results appear to reinforce the idea that Republican women prioritizing positive party cohesion messaging to overcome inparty barriers, particularly due to the significant demonstration of party platform focused advertisements.

Republican and Democratic Policy Messaging

The Republican and Democratic policy trait subsets are detailed in Figures 2A-2F and Figures 3A-C, respectively. Figures 2A-2C display frequencies for Republican women, and results for male Republican candidates are displayed in figures 2D-2F. Figures 3A-3C are representative of Democratic female candidates. Democratic male candidates utilized policy issue messaging at generally similar rates compared to their female counterparts, although they displayed moderately higher levels of issue messaging in relation to healthcare and economic policy issues. Overall, the variances are interesting, but do not necessarily comport meaning to the analysis at hand; thus, only the Democratic female sample measurements will be evaluated along with the Republican candidate groups, with the acknowledgment that the Democratic in-group variances could provide a further source of study and analysis. The first subset of policy traits for the Republican set relates to National Security Issues (Figure 2A for Republican women and Figure 2D for Republican men). The highest frequency distributions relate to immigration and military for

Figure 2A. Republican Issue Messaging: National Security Republican Women

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Polarization and Party Cohesion in Campaign Messaging / Female Republican Senate Candidates

Figure 2B. Republican Issue Messaging: Economy Republican Women

None of These Issues Mentioned

Taxes, Entitlement and Healthcare Reform

Taxes and Healthcare Reform

Entitlement and Healthcare Reform

Taxes and Entitlement Reform

Healthcare Reform

Entitlement Reform

Taxes/Tax Cuts

Figure 2C. Republican Issue Messaging: Social Issues Republican Women

Figure 2D. Republican Issue Messaging: National Security Republican Men

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Figure 2E. Republican Issue Messaging: Economy Republican Men

Figure 2F. Republican Issue Messaging: Social Issues Republican Men

female Republican candidates, and national security/military for male Republican candidates (this excludes code 8 relating to no mention of issues). Female Republican candidates demonstrate remarkably higher levels of Republican policy and issue messaging than Republican males, with 53.3% of their campaign advertisements containing explicit messaging relating to core Republican policies (within the National Security subset). The percentage for advertisements coded for explicit National Security Issue messaging within the Republican male sample was 19.2%. It is important to note that, as Cassese and Holman’s (2018) study and Lawless’ (2004) study assert, these are all masculine policy traits. Figures 2B (female sample) and 2E (male sample) demonstrate the frequencies for codes within the Economic Issues subset for Republican policy traits. Tax cuts and entitlement/healthcare reform receive the greatest frequencies among the male and female Republican groups (again, code 26

8 representing no issues mentioned is not included in the frequency comparison), with Republican female candidates maintaining the highest overall percentage of advertisements utilizing explicit Republican Economic Issues messaging at 44.4%. The overall percentage for advertisements with policy messaging in the Economic Issues subset among Republican male candidates was 30.8%. Finally, Figures 2C and 2F (Republican women and men, respectively) display the results for the Social Issues policy subset for Republican policy traits. For codes relating to explicit policy mentions, family values received the highest frequency distribution among female Republican candidates at 15.6%, with an overall percentage (for advertisements with explicit policy messaging) of 33.8%. No single Social Issue messaging code accounted for more than 3.8% of the Republican male candidates’ advertisements, and the overall percentage of advertisements with express Social Issue messaging was 11.5%.

Polarization and Party Cohesion in Campaign Messaging / Female Republican Senate Candidates

Figure 3A. Democratic Issue Messaging: Education and Healthcare Democratic Women

Figure 3B. Democratic Issue Messaging: Economy Democratic Women

Figure 3C. Democratic Issue Messaging: Social Issues Democratic Women

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Democratic policy and issue messaging subsets are displayed in Figures 3A-C. While the first policy trait subsets for both the Republican and Democratic policies (National Security and Education/Healthcare, respectively) result in close distributions of issue areas from codes 1 through 7 (again, no mention received the greatest distribution across the board, so closer analysis must be done within the explicit codes), Republican policy trait messaging receives higher frequency distributions on all three counts. Between Republican National Security and Democratic Education and Healthcare policy subsets, Republican policies are explicitly mentioned in 53.3% of all female Republican campaign advertisements (National Security subset), while 43.6% of campaign advertisements from the female Democratic group employ explicit policy messaging (for the Education and Healthcare subset). The second policy subsets, Republican Economic Issues and Democratic Economic Issues, demonstrate a significant disparity, as Republican Economic policies receive explicit mentions at an overall percentage of 44.4% and Democratic Economic policies are explicitly mentioned in only 14.5% of campaign advertisements. Similar findings result in the third policy subset, with Republican Social Issues coded in 33.3% (overall percentage of all Social Issue Republican codes) of female Republican candidates’ advertisements, and Democratic Social Issues coded in an aggregate of 14.5% of Democratic female candidates’ advertisements.

Non-Policy Messaging

The results of the variables for Support of President Trump’s Agenda, Ideology Messaging, Bipartisanship, and Qualification Messaging are also noteworthy. By evaluating the code frequencies in relation to partisan and gender groups, additional evidence of higher levels of party cohesion messaging among female Republican candidates is rendered. Among male and female Republican candidates, female Republican candidates employed messaging relating to Support for President Trump’s Agenda at considerably higher rates. While 33.3% of female Republican candidates’ advertisements demonstrated “Strong Support for Trump,” 7.7% of male Republican advertisements were classified as conveying strong Trump support messaging, and another 7.7% were coded as relating moderate Trump support messaging. Democratic female candidates displayed very marginal frequencies of support for Trump messaging, with 3.6% of advertisements conveying moderate support for Trump messaging, and another 3.6% coded for weak support of Trump messaging. The distribution for Ideology Messaging shows the greatest frequency of conservative ideology messaging distributed toward female Republican candidates as well, with 46.7% of their sample coded for conservative values messaging. Campaign advertisements from the Republican male group conveyed conservative values messaging in 38.5% of the sample. Democratic female candidates demonstrated conservative values messaging in 1.8% of their advertisement set, and moderate values messaging in another 7.3%. The 28

distribution of frequencies for Bipartisanship Messaging reveals further evidence of female Republicans engaging in messaging to convey unwavering conservativism. Twenty percent of female Republican candidates’ advertisements displayed messaging relating to unwillingness to engage in bipartisanship (“candidate will not engage in bipartisanship” code 2). Only 7.7% of male Republicans advertisements demonstrated nonbipartisanship messaging. Unsurprisingly, 43.6% of female Democratic candidates’ advertisements communicated willingness to engage in bipartisanship (“candidate will engage in bipartisanship”), further demonstrating the ability of Democratic female candidates to present themselves as relatively independent within their party. The frequency distributions relating to Qualification Messaging are extremely interesting, and perhaps present another avenue for further research. Female candidates from both Republican and Democratic candidate samples utilized higher rates of political career and/or partisan qualification, with female Republicans utilizing qualification messaging relating to political career experience in 37.8% of the sample, along with another 11.1% coded for qualification messaging related to private sector career experience. Democratic female candidates demonstrated high levels of political and/or partisan qualification messaging among 34.5% of the sample. None of the female Democratic candidate advertisements demonstrated private sector career qualification messaging. Male Republican candidates received fewer qualification messaging code frequencies than both of the female candidate groups, with only 25% coded as conveying political and/or partisan qualification messaging, and a mere 5.8% relating private sector career qualification messaging. Democratic male candidates utilized the highest rate of Qualification Messaging, with 56.3% of the sample demonstrating political and/or partisan qualification messaging. Indeed, the frequency analysis for the Qualification Messaging variable could very well provide additional queries for further research. Overall, these results, in combination with those from the partisan support and opposition variables and the Republican and Democratic policy trait area variables, demonstrate rather clearly that more evidence of party cohesion messaging is readily available in the campaign advertisements of female Republican U.S. Senate candidates as compared to their female Democratic and male Republican counterparts.

CONCLUSION Hayes and Lawless’ (2016, 19) study noted that “As the parties have grown further apart in recent decades [partisan polarization], they have also become internally more cohesive, with Republicans becoming more reliably conservative…in a polarized system, party exerts a stronger influence.” Given the effects of asymmetric partisan polarization at the elite level of the Republican Party, it would be reasonable to expect to find an increased utilization of party cohesion messaging within the

Polarization and Party Cohesion in Campaign Messaging / Female Republican Senate Candidates

multi-media digital campaign advertisements of Republican Party candidates in general. While Republican men demonstrate various elements of party cohesion messaging within their campaign messaging and advertisements, they are inherently advantaged over their female counterparts by the internal structure, political, and cultural norms and dynamics of the Republican Party (Wineinger 2018). This content analysis sought to determine whether this interplay of partisan dynamics and gendered trait stereotypes leads female Republican candidates— specifically, U.S. Senate candidates— to rely more heavily on party cohesion messaging in their campaign advertisements. The findings of the content analysis demonstrate that female Republican candidates are utilizing party cohesion messaging within their multi-media digital campaign advertisements at a significantly greater rate than both female Democratic candidates and their male co-partisans. By comparing the multi-media digital campaign advertising of male and female candidates of both the Republican and Democratic Parties, the differences relating to party cohesion messaging within Republican female candidates’ advertisements can reasonably be attributed to factors of both gender and partisanship. Measurement results for variables such as Party Support, Party Opposition, Focus of Advertisement, Ideology Messaging, Bipartisanship, and Support of President Trump revealed that female Republican candidates employed candidate-centric (generally avoiding attack ads) messaging relating to strong party support and conservative ideology. Additionally, female Republicans’ advertisements incorporated core partisan platform policy messaging at considerably higher rates than those of male Republicans and female Democrats. Ultimately, these findings demonstrate that Republican women are more intentional than both male Republicans and Democratic women in conveying themselves as strong Republican partisan adherents and strong conservatives, maintaining the focus of their messaging on themselves as qualified, conservative candidates. Democratic and Republican women exhibited fewer degrees of variance on variables such as Focus of Advertisement and Qualification Messaging (with the exception of Republican females significantly greater employment of party platform messaging); however, male Republican candidates displayed considerably increased utilization of partisan opposition and opponent-focused opposition messaging. This further confirms the findings of prior studies regarding gendered trait stereotypes and campaign advertising (Cassese and Holman 2018). Because the Democratic Party prioritizes identity and group political coalitions, along with championing feminine gendered policies within its policy platform, female Democratic candidates do not find themselves needing to overcome gendered policy trait biases at the levels Republican women do (Cassese and Holman 2018; Wineinger 2018). As previously noted, female Republican candidates must overcome the barriers of gendered trait stereotypes and internal structural and cultural norms within their own party, and the results of this content analysis provide reasonable evidence that they are endeavoring to do

so through deliberate party cohesion messaging through their multi-media digital campaign advertising. Although the size and scope of this analysis is considerably limited, it is important that research in this vein continues. The campaign advertisements that were content analyzed for this study were limited to a comparatively small population of campaign advertisements, both regarding the candidate pools, number of advertisements, and media format of advertisements. Time-bound limitations also constrain the scope of this research, as only U.S. Senate campaign advertisements from the 2018 midterm election were utilized. Further research and analysis should seek to study larger populations of male and female candidates from both the Republican and Democratic parties across a greater span of time and a greater variety of electoral races, in order to determine if party cohesion messaging has always been more prevalent in the campaign advertisements of female Republican candidates, or if the trend began more recently. If a definitive starting point for this prevalence of party cohesion messaging can be ascertained, additional research should also be conducted to discern whether the use of party cohesion messaging among female Republicans are continuing to increase across time. These findings about differences in party cohesion messaging on feminine policy trait issues between Democratic males and females, as well as those relating to Qualification Messaging, merit further investigation. Are male candidates within the Democratic Party similarly impacted by feminine policy stereotypes (as compared to Republican female candidates on masculine policy stereotypes)? Answering this query would certainly add considerable depth and value to existing scholarship on gendered stereotypes and candidate evaluations in the context of both the major political parties. Continued research and analysis of the results regarding Qualification Messaging would provide further insight into the dynamic interaction of gendered partisan differences in campaign messaging. Ultimately, through expanding the body of literature regarding the broad effects of partisan polarization, gender stereotypes, and gendered candidate evaluations, a more accurate understanding of the causes and future implications of underrepresentation of women within the Republican Party can be developed (Swers 2018). n

REFERENCES Ballotopedia. 2018. “United States Senate Elections, 2018. Ballotopedia.org. https://ballotpedia.org/United_States_ Senate_elections,_2018 (Accessed July 1, 2019). Cassese, Erin C., and Mirya R. Holman. 2018. “Party and Gender Stereotypes in Campaign Attacks.” Political Behavior 40(3): 785–807. Center for American Women and Politics. 2018. http://www.cawp. rutgers.edu/ (Accessed April 25, 2019). Deckman, Melissa. 2018. “Women in the Tea Party and the GOP: A Natural Alliance?” In The Right Women: Republican Party Activists,

Pi Sigma Alpha Undergraduate Journal of Politics Candidates, and Legislators, eds. Malliga Och and Shauna L. Shames, 247-258. Santa Barbara, CA: Praeger Democratic Platform Committee. 2016. “2016 Democratic Party Platform.” 2016. https://democrats.org/wp-content/ uploads/2018/10/2016_DNC_Platform.pdf. (Accessed July 2, 2019). Dolan, Kathleen. 2010. “The Impact of Gender Stereotyped Evaluations on Support for Women Candidates.” Political Behavior 32(1): 69–88.

Swers, Michele. 2018. “From the Republican Revolution to the Tea Party Wave: Republican Women and the Politics of Women’s Issues.” In The Right Women: Republican Party Activists, Candidates, and Legislators, eds. Malliga Och and Shauna L. Shames, 199-228. Santa Barbara, CA: Praeger. Theodoridis, Alexander G. 2017. “Me, Myself, and (I), (D), or (R)? Partisanship and Political Cognition through the Lens of Implicit Identity.” The Journal of Politics 79(4): 1253–67.

Dolan, Kathleen A. 2014. When Does Gender Matter? Women Candidates and Gender Stereotypes in American Elections. Oxford: Oxford University Press.

Todd, Chuck, Mark Murray, and Carrie Dann. 2018. “Midterms 2018: It Was the Year of the Woman - For Democrats, Not Republicans.” NBCNews.com. https://www.nbcnews.com/politics/ first-read/it-was-year-woman-not-republican-side-n938341 (Accessed December 1, 2018).

Fiorina, Morris P. 2017. Unstable Majorities: Polarization, Party Sorting, and Political Stalemate. Stanford, CA: Hoover Institution Press.

U.S. Political Adverts. YouTube. https://www.youtube.com/channel/ UCk6o_KK-rwNWyuGQUXTExUw/videos (Accessed June 15, 2019).

Fowler, Erika Franklin, Michael Franz, and Travis N. Ridout. 2018. “The Big Lessons of Political Advertising in 2018.” The Conversation. https://theconversation.com/the-big-lessons-ofpolitical-advertising-in-2018-107673 (Accessed June 20, 2019).

Wineinger, Catherine. 2018. “Gendering Republican Party Culture.” In The Right Women: Republican Party Activists, Candidates, and Legislators, eds. Malliga Och and Shauna L. Shames, 25-49. Santa Barbara, CA: Praeger.

Fox, Richard L., and Jennifer L. Lawless. 2004. “Entering the Arena? Gender and the Decision to Run for Office.” American Journal of Political Science 48(2): 264–80. Hall, Andrew B., and Daniel M. Thompson. 2018. “Who Punishes Extremist Nominees? Candidate Ideology and Turning Out the Base in US Elections.” American Political Science Review 112(3): 509–24. Hayes, Danny, and Jennifer L. Lawless. 2016. Women On The Run: Gender, Media, and Political Campaigns in a Polarized Era. New York, NY: Cambridge University Press. Lawless, Jennifer L. 2004. “Women, War, and Winning Elections: Gender Stereotyping in the Post-September 11th Era.” Political Research Quarterly 57 (3): 479–90. Lawless, Jennifer L., and Kathryn Pearson. 2008. “The Primary Reason for Women’s Underrepresentation? Reevaluating the Conventional Wisdom.” The Journal of Politics 70(1): 67–82. Och, Malliga, and Shauna Lani Shames. 2018. The Right Women: Republican Party Activists, Candidates, and Legislators. Santa Barbara, CA: Praeger. Peterson, Erik. 2017. “The Role of the Information Environment in Partisan Voting.” The Journal of Politics 79(4): 1191–1204. Philpot, Tasha S., and Hanes Walton. 2007. “One of Our Own: Black Female Candidates and The Voters Who Support Them.” American Journal of Political Science 51(1): 49–62. Sanbonmatsu, Kira, and Kathleen Dolan. 2009. “Do Gender Stereotypes Transcend Party?” Political Research Quarterly 62(3): 485–94. Schreiber, Ronnee. 2018. “Republican Party Politics, Women’s Electoral Fortunes, and the Myth of Gender Neutrality.” In The Right Women: Republican Party Activists, Candidates, and Legislators, eds. Malliga Och and Shauna L. Shames, 247-258. Santa Barbara, CA: Praeger. Schwartz, Ian. 2018. “Bob Corker: Supporting Trump Is Becoming a Cultish Thing.” RealClearPolitics. https://www.realclearpolitics. com/video/2018/06/13/corker_supporting_trump_is_ becoming_a_cultish_thing.html. (Accessed November 18, 2018). 30

NOTES 1. The YouTube page, “U.S. Political Adverts” (https://www.youtube. com/channel/UCk6o_KK-rwNWyuGQUXTExUw/videos), is a repository of multi-media campaign advertisements independently managed by individuals. All advertisements that are uploaded to the page are generally kept indefinitely unless they are requested to be removed by a candidate’s campaign management (advertisements that were previously viewed for Kirsten Gillibrand and Deb Fischer have since been removed). The campaign advertisements are from United States Senate and House races for the 2018 midterm elections, as well as from 2018 gubernatorial elections and some more recently released 2020 presidential primary candidates’ primary campaigns. The vast majority of advertisements that have been uploaded were viewable as television campaign advertisements in their respective local markets, although some were only viewable online (whether on YouTube as digital ads or paid ads on social media). A very small portion of the advertisements (less than ten) had to be viewed directly on either the candidate’s YouTube channel/page or campaign website. For this reason, this study references the campaign advertisements viewed through this repository and other online sources (candidate YouTube channels and/or campaign websites) as multi-media digital advertisements. 2. The variable relating specifically to the candidate’s identity, U.S. Senate Candidate, the Kappa is 1.00. Partisan Affiliation variables received a kappa score of 0.959, and the Incumbency variable resulted in a kappa score of 0.968. The Focus of Advertisement variable received a kappa score of 0.842. The Party Support Messaging variable resulted in 0.777. Party Opposition Messaging variables are 0.820. The kappa scores for the Republican Policy/Issue Messaging variables are 0.857, 0.825, and 0.639, respectively. Reliability kappa scores for the three Democratic Policy/Issue Messaging variables are 0.825, 0.738, and 0.826, respectively. The reliability kappa score for the Support of Trump’s Agenda variable is 0.819, and the Ideology Messaging variable received a reliability kappa score of 0.683. Lastly, the Bipartisanship Messaging variable received a 0.790, and the Qualification Messaging variable received a 0.926 kappa score.

Polarization and Party Cohesion in Campaign Messaging / Female Republican Senate Candidates

APPENDIX: CODEBOOK Variable Format

Variable

US Senate Candidate Partisan Affliliation Incumbency Focus of Advertisement US Senate Candidate Party Support Messaging Partisan Affliliation Incumbency Party Opposition Messaging Focus of Advertisement Party Support Messaging Republican Issue Messaging National Security Party Opposition Messaging

Format

Numeric Identifier Numeric Identifier Numeric Identifier Numeric Identifier Numeric Identifier Numerical Range Numeric Identifier Numeric Identifier Numerical Range Numeric Identifier Numerical Range Numeric Identifier Numerical Range

Republican Issue Messaging Republican Issue Messaging Economy National Security

Numeric Identifier Numeric Identifier

Republican Issue Messaging Republican Issue Messaging Social Issues Economy

Numerical Identifier Numeric Identifier

Democratic Issue Messaging Republican Issue Messaging Health and Education Social Issues

Numeric Identifier Numerical Identifier

Democratic Issue Messaging Democratic Issue Messaging Health and Education Economy

Numeric Identifier Numeric Identifier

Democratic Issue Messaging Democratic Issue Messaging Economy Social Issues

Numeric Identifier Numeric Identifier

Support of Trump Agenda Democratic Issue Messaging Ideology Messaging Social Issues

Numerical Range Numeric Identifier Numeric Identifier

Bipartisanship Support of Trump Agenda Ideology Messaging Qualification Messaging

Numeric Identifier Numerical Range Numeric Identifier Numerica Identifier

Bipartisanship

Numeric Identifier

Qualification Messaging

Numerica Identifier

Variable Label

Variable Label Martha McSally=1; Kyrsten Sinema=2; Karin Housely=3; Tina Smith=4; Kirsten Gillibrand=5; Chele C. Farley=6; Marsha Blackburn=7; Deb Fischer=8; Heidi Heitkamp=9; Leah Vukmir=10; Cindy Hyde-Smith=11; Susan Hutchison=12; Claire McCaskill=13; Jenny Wilson=14; Tammy Baldwin=15; Jacklyn Rosen=16; Dean Heller=17; Tim Kaine=18; Rick Scott=19; Phil Bredesen=20; Josh Hawley=21; Bob Casey=22; Kevin Cramer=23; Sherrod Brown=24; Martha McSally=1; Kyrsten Sinema=2; Karin Housely=3; Tina Smith=4; Kirsten Gillibrand=5; Chele C. Farley=6; John Barrasso=25; Joe Manchin=26; Roger Wicker=27; Sheldon Whitehouse=28; Ted Cruz=29; Bill Nelson=30; Marsha Blackburn=7; Deb Fischer=8; Heidi Heitkamp=9; Leah Vukmir=10; Cindy Hyde-Smith=11; Susan Patrick Morrisey=31; Jon Tester=32 Hutchison=12; Claire McCaskill=13; Jenny Wilson=14; Tammy Baldwin=15; Jacklyn Rosen=16; Dean Heller=17; Tim Democrat=1; Republican=2 Kaine=18; Rick Scott=19; Phil Bredesen=20; Josh Hawley=21; Bob Casey=22; Kevin Cramer=23; Sherrod Brown=24; Challenger=1; Incumbent=2; Open Race=3 John Barrasso=25; Joe Manchin=26; Roger Wicker=27; Sheldon Whitehouse=28; Ted Cruz=29; Bill Nelson=30; Candidate=1; Opponent=2; Party Platform=3 Patrick Morrisey=31; Jon Tester=32 Strong Democrat=1; Democrat=2; Strong Republican=3; Republican=4; No Explicit Mention of Party=5 Democrat=1; Republican=2 Strong Anti-Democrat=1; Anti-Democrat=2; Strong Anti-Republcan=3; Anti-Republican=4; No mention of Challenger=1; Incumbent=2; Open Race=3 opposition party=5 Candidate=1; Opponent=2; Party Platform=3 Immigration/Wall=1; Gun Rights/2nd Amendment=2; National Security/Military=3; Immigration and Gun Strong Democrat=1; Democrat=2; Strong Republican=3; Republican=4; No Explicit Mention of Party=5 Rights=4; Gun Rights and Military =5; Immigration and Military=6; Immigration/Gun Rights/Military=7; None of Strong Anti-Democrat=1; Anti-Democrat=2; Strong Anti-Republcan=3; Anti-Republican=4; No mention of these=8 opposition party=5 Taxes/Tax Cuts=1; Entitlement Reform=2; Healthcare Reform=3; Taxes and Entitlement Reform=4; Entitlement Immigration/Wall=1; Gun Rights/2nd Amendment=2; National Security/Military=3; Immigration and Gun Reform and Healthcare Reform=5; Taxes and Healthcare Reform=6; Taxes/Entitlement Reform/Healthcare Rights=4; Gun Rights and Military =5; Immigration and Military=6; Immigration/Gun Rights/Military=7; None of Reform=7; None of these=8 these=8 Taxes/Tax Cuts=1; Entitlement Reform=2; Healthcare Reform=3; Taxes and Entitlement Reform=4; Entitlement Pro-Life=1; Religious Freedom=2; Family Values=3; Pro-Life and Family Values=4; Religious Freedom and Family Reform and Healthcare Reform=5; Taxes and Healthcare Reform=6; Taxes/Entitlement Reform/Healthcare Values=5; Pro-Life and Religious Freedom=6; Pro-Life/Religious Freedom/Family Values=7; None of these=8 Reform=7; None of these=8 Education/STEM Improvements=1; Healthcare Expansion=2; Opioid Crisis=3; Education/STEM Improvements and Healthcare Expansion=4; Healthcare Expansion and Opioid Crisis=5; Education/STEM Improvements and Opioid Pro-Life=1; Religious Freedom=2; Family Values=3; Pro-Life and Family Values=4; Religious Freedom and Family Crisis=6; Education/STEM Improvements, Healthcare Expansion, and Opioid Crisis=7; None of these=8 Values=5; Pro-Life and Religious Freedom=6; Pro-Life/Religious Freedom/Family Values=7; None of these=8 Fiscal Transparency=1; Social Welfare/Entitlements=2; Living/Equitable Wage=3; Fiscal Transparency and Social Education/STEM Improvements=1; Healthcare Expansion=2; Opioid Crisis=3; Education/STEM Improvements and Welfare/Entitlements=4; Social Welfare/Entitlements and Living/Equitable Wage=5; Fiscal Transparency and Healthcare Expansion=4; Healthcare Expansion and Opioid Crisis=5; Education/STEM Improvements and Opioid Living/Equitable Wage=6; Fiscal Transparency, Social Welfare/Entitlements, and Living/Equitable Wage=7; None Crisis=6; Education/STEM Improvements, Healthcare Expansion, and Opioid Crisis=7; None of these=8 of these=8 Fiscal Transparency=1; Social Welfare/Entitlements=2; Living/Equitable Wage=3; Fiscal Transparency and Social Pro-Choice=1; Racial/Gender/LGBTQ Equality=2; Sexual Harassment/Me Too=3; Pro-Choice and Welfare/Entitlements=4; Social Welfare/Entitlements and Living/Equitable Wage=5; Fiscal Transparency and Racial/Gender/LGBTQ Equality=4; Racial/Gender/LGBTQ Equality and Sexual Harassment/Me Too=5; Pro-Choice Living/Equitable Wage=6; Fiscal Transparency, Social Welfare/Entitlements, and Living/Equitable Wage=7; None and Sexual Harassment/Me Too=6; Pro-Choice/Racial, Gender, LGBTQ Equality/Sexual Harassment, Me Too=7; of these=8 None of these=8 Pro-Choice=1; Racial/Gender/LGBTQ Equality=2; Sexual Harassment/Me Too=3; Pro-Choice and Strong Trump Supporter=1; Moderate Trump Supporter=2; Weak Trump Supporter=3; Non-Supporter=4; No Racial/Gender/LGBTQ Equality=4; Racial/Gender/LGBTQ Equality and Sexual Harassment/Me Too=5; Pro-Choice Mention of Trump=5 and Sexual Harassment/Me Too=6; Pro-Choice/Racial, Gender, LGBTQ Equality/Sexual Harassment, Me Too=7; Conservative values=1; Liberal values=2; Moderate values=3; No mention of ideology=4 None of these=8 Candidate will engage in bipartisanship=1; Candidate will promote party agenda (no bipartisanship)=2; No Strong Trump Supporter=1; Moderate Trump Supporter=2; Weak Trump Supporter=3; Non-Supporter=4; No mention of bipartisanship or non-bipartisanship=3 Mention of Trump=5 Candidate mentions career qualification=1; Candidate mentions political career/partisan qualification=2; No Conservative values=1; Liberal values=2; Moderate values=3; No mention of ideology=4 mention of candidate qualification=3 Candidate will engage in bipartisanship=1; Candidate will promote party agenda (no bipartisanship)=2; No mention of bipartisanship or non-bipartisanship=3 Candidate mentions career qualification=1; Candidate mentions political career/partisan qualification=2; No ÂŠ Pi Sigma Alpha 2019 31 mention of candidate qualification=3

Pi Sigma Alpha Undergraduate Journal of Politics

Reluctance to Express Vote Choice among Ohioans during the 2016 U.S. Presidential Election Andrew Henthorn, Baldwin Wallace University Donald Trump’s surprise victory in the 2016 U.S. presidential election led many to wonder about the possibility of “shy” Trump voters, or voters who were reluctant to voice their support for the unconventional candidate. Using original postelection survey data (N = 1,019), this paper examines whether Trump voters were more reluctant than other voters to express their support for their preferred candidate. The findings indicate that those who supported Trump were not more reluctant to share their vote choice. However, women, younger people, and those who were better educated were significantly more reluctant to share their vote choice. These findings suggest that certain segments of the electorate were more reluctant than others to express their vote choice, but that this reluctance was not structured by vote choice. These findings are important in understanding the extent to which social desirability bias plays a role in pre-election polls.

INTRODUCTION uring the 2016 U.S. presidential election, many election forecasts predicted a comfortable win for the Democratic presidential candidate Hillary Clinton (Bialik 2016; Klar, Weber, and Krupnikov 2016; Darling 2017; Enten 2016; Goldmacher and Schreckinger 2016; Mercer, Deane, and McGeeney 2016; Tamman 2016; Wright and Wright 2018). Although Clinton won the national popular vote by nearly three million votes, Republican presidential candidate Donald J. Trump carried the Electoral College by 304 to 227 votes (United States Federal Election Commission 2017). In doing so, Trump pulled off one of the largest upsets in United States’ election history (Goldmacher and Schreckinger 2016). For instance, Anthony Zurcher of BBC News described Trump’s win as “unexpected by most and incomprehensible to many” (Zurcher 2016, para. 4). Similarly, in an article for the Columbus Dispatch political scientist Paul Beck stated, “It was a stunning outcome. No one really anticipated it, even the Trump people” (Rowland and Wehrman 2016, para. 15). These sentiments, and others like them, made survey practitioners, pundits, and scholars alike question where the polls and election forecasts went wrong. How did so many pollsters fail to predict the outcome of the election, especially in the battleground and bellwether state of Ohio, as well as other Midwestern states such as Wisconsin and Michigan? This paper examines one explanation in particular: social desirability bias, or whether some voters were more reluctant than others to express their true preference for president in pre-election polls (Dillman, Smyth, and Christian 2014, ch. 4). Specifically, it is hypothesized that people who voted for

Trump were more reluctant than people who voted for other candidates to share their vote choice. To test this expectation, original, post-election survey data collected between February 24, 2017, and March 8, 2017, in the battleground and bellwether state of Ohio (N = 1,019) were examined. Surprisingly, findings show that Trump voters were not more reluctant than people who supported other candidates to express support for their vote choice. At the same time, certain segments of the Ohio electorate were more reluctant than others to tell people for whom they were going to vote. These findings are important because they speak to larger debates in public opinion research about social desirability bias.

Background Social Desirability Bias in Public Opinion Research

In the weeks prior to the 2016 U.S. presidential election, public opinion polls overestimated support for Democratic candidate Hilary Clinton and underestimated support for Republican candidate Donald J. Trump (Enns, Lagodny, and Schuldt 2017). Some of the confusion resulted from the use of national polls, which predict the outcome of the national popular vote but not the outcome of the Electoral College. This distinction is important because candidates must win 270 votes in the Electoral College, not the national popular vote, to win the presidency. At the state level, pre-election polls suggested that the race between Clinton and Trump was much closer, but many polls still gave Clinton an edge (Desilver 2017; Estepa 2017). Although the discrepancy between polls conducted at the national and state levels is beyond the scope of this study, both types of polls may have underestimated support for

Reluctance to Express Vote Choice among Ohioans during the 2016 U.S. Presidential Election

Trump because of social desirability bias. Social desirability bias effects occur when respondents feel that one answer to a public opinion poll is more acceptable (i.e., more socially desirable) than another (Dillman, Smyth, and Christian2014, ch. 4). As a result, respondents may not indicate their true preference, or they may withhold their opinion completely (Dillman, Smyth, and Christian. 2014, chapter 4). Survey researchers noticed social desirability bias effects most prominently in the 1982 California governor’s race between an African-American candidate, Democrat Tom Bradley, and a white candidate, Republican George Deukmejian (Levin 2008). Although Bradley was ahead in pre-election polls, he ultimately lost the race. Consequently, many concluded that voters did not want to tell interviewers they would vote against an African-American candidate (Gray, O’Shea, Cohen, and Wolfe 2016). This phenomenon, known as the “Bradley Effect,” is not just limited to race; it extends to other demographic characteristics as well (Gray, O’Shea, Cohen, and Wolfe 2016), and might have explained discrepancies between pre-election polls during the 2016 U.S. presidential election and the actual outcome.

Social Desirability Bias and the 2016 U.S. Presidential Election

Voters may have been reluctant to express their support for Trump in pre-election polls for several reasons. Above all, Trump was quick to make offensive or derogatory statements on the campaign trail about many segments of the electorate, including immigrants; Muslims; and women, including Democratic opponent Hillary Clinton. In his campaign announcement, for instance, Trump referred to some Mexican immigrants as drug dealers, criminals, and rapists (Time Staff 2015). Specifically, Trump claimed: When Mexico sends its people, they’re not sending their best… They’re sending people that have lots of problems, and they’re bringing those problems with us. They’re bringing drugs. They’re bringing crime. They’re rapists. And some, I assume, are good people (Time Staff 2015, para. 9). Furthermore, in response to a question on immigration and border security during the third presidential debate, Trump said: “We have some bad hombres here, and we’re going to get them out” (Zezima 2016). In doing so, Trump implied that (Mexican-American) immigrants were a threat to public safety. During the campaign, Trump implied that Muslims were a threat to national security. After a mass shooting in San Bernadino, California, Trump’s campaign issued a press release, which stated “Donald J. Trump is calling for a total and complete shutdown of Muslims entering the United States until our country’s representatives can figure out what is going on” (Vitali 2016, para. 5). Trump also suggested that mosques

could be monitored and even closed to combat domestic terrorism (Vitali 2016). In addition to racial and ethnic slurs, Trump made disrespectful statements about women. During a Republican primary debate, for instance, moderator Megyn Kelly of FOX News asked Trump about derogatory comments he had made about women. After the debate, Trump claimed, “There was blood coming out of her [Kelly’s] eyes, blood coming out of her wherever” (Chavez, Stracqualursi, and Keneally 2016, para. 6). Trump also utilized gendered insults against his Democratic opponent. Towards the end of the third presidential debate, for example, Trump called Clinton a “nasty woman” (Politico Staff 2016, para. 246). This comment called into question the extent to which Trump respected women (Meyers 2016). Trump’s attitudes towards and treatment of women also came into question when the Access Hollywood tapes were released a few weeks before the general election. In these tapes, one of Trump’s less offensive comments was as follows: Yeah, that’s her. With the gold. I better use some Tic Tacs just in case I start kissing her. You know, I’m automatically attracted to beautiful — I just start kissing them. It’s like a magnet. Just kiss. I don’t even wait. And when you’re a star, they let you do it. You can do anything (Bullock 2016, para. 17). Collectively, Trump’s comments caused a widespread backlash against his campaign and may have made women less inclined to vocalize their support for the Republican candidate. Trump’s candidacy was also controversial because many people questioned whether Trump had the temperament and judgment to be president. Critics included members of the Republican establishment, national security officials, conservative pundits, and voters alike. For example, during the opening of the 2016 Republican National Convention in Cleveland, Ohio, members of a handful of state delegations, led by Utah, moved to force a roll-call vote on the rules of the convention, hoping to allow delegates to vote for whichever candidate they preferred, even if they were bound to vote for Trump based on the results of the primary in their state (CNN Wire 2016). In addition, after Trump secured the nomination, 50 of the country’s most senior Republican national security advisers penned a letter in which they stated that Trump “‘lacks the character, values, and experience’ to be president and ‘would put at risk our country’s national security and well-being’” (Sanger and Haberman 2016, para. 1). Conservative pundits also questioned Trump’s fitness to be president. For example, David Ross Meyers of FOX News wrote, “Trump lacks the judgment, character, and emotional stability to be president. Given his frequent public outbursts and lack of self-restraint, the thought of Mr. Trump controlling our military and nuclear weapons is unacceptable” (Meyers 2016, para. 7). In other words, Meyers questioned Trump’s ability to handle the responsibilities of the office

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and questioned his fitness to serve in this role. Finally, voters themselves questioned whether Trump had the temperament to serve as president. Before the election, for instance, only 17% of voters believed that Trump had the temperament to serve as president (Hartig, Lapinski, and Psyllos 2016). To summarize, people who supported the Republican Party’s nominee for president may have been reluctant to express their support because of Trump’s behavior before and during the campaign. To be sure, Clinton’s campaign was not without controversy. For instance, she once referred to Trump’s supporters as “deplorables” (Reilly 2016). For the most part, however, Clinton’s bid for the presidency was much more characteristic of a traditional political campaign (Cillizza 2017). As a result, voters who preferred the Republican candidate may have been unwilling to express their support in public opinion polls. If so, polls would have underestimated support for Trump.

Literature Review Reluctance to Share Vote Choice in the 2016 U.S. Presidential Election

Since the 2016 presidential election, a growing body of research has examined whether Trump supporters were reluctant to express their support. However, the literature is divided as to whether there was social desirability bias in preelection polls. As previously defined, social desirability bias effects occur when respondents feel that one answer to a public opinion poll is more acceptable (i.e., socially desirable) than another (Dillman, Smyth, and Christian 2014, ch. 4). In the next section, I review the evidence on this point. On the one hand, several studies suggest that people may have masked their true candidate preference when surveyed. For instance, Klar, Weber, and Krupnikov (2016) used a college-student sample to examine whether people who were more prone to social desirability bias (i.e., likely to change their behavior in social settings) were more reluctant to express support for Trump. They found that those who had higher self-monitoring scores, or people who were “more likely to adjust their behaviors to comply with social norms,” were less likely to express support for Trump than those with lower self-monitoring scores (Klar, Weber, and Krupnikov 2016, 433). In another study, employing a nationally representative sample, Enns and Schuldt (2016) found that people were more likely to express support for Trump’s stance on immigration if Trump’s name was not attached to the policy statement. The authors concluded that the latter finding suggested that there was “hidden” support for Trump. Enns, Lagodny, and Schuldt (2017) also found evidence of “hidden” Trump voters in state and national polls. Specifically, voters who indicated that they were voting for a Republican candidate for the U.S. Senate were more likely to report that they were undecided in the presidential race, which suggests that “undecided” voters ultimately voted for Trump. In addition, Brownback 34

and Novotny (2018, 39) conducted three survey experiments to determine whether respondents were reluctant to report whether they “often” found themselves “agreeing with Donald Trump” or “agreeing with Hillary Clinton,” depending on the treatment to which they were assigned. Using list experiments, which allow respondents to indicate the number of statements with which they agree instead of the specific items with which they agree (Glynn 2013), and direct questions about the extent to which respondents agreed with the candidates, the authors found that respondents were more likely to report agreement with Clinton than with Trump when they could not hide their preference (i.e., when respondents could not conceal their preference through a list experiment). Collectively, these studies suggest that people were reluctant to express their support for Trump. As a result, it could be argued that pre-election polls may have underestimated support for Trump. In contrast, however, other studies have not found evidence of social desirability bias in pre-election polls for the 2016 U.S. presidential election. For instance, Enten (2016) compared statewide election polls to the respective election results in each state. The author concluded there were not “shy,” or hidden Trump voters because Trump outperformed pre-election polls in conservative states and underperformed in more liberal states. Other researchers have also found no evidence of social desirability bias in pre-election polls. Comparing a list experiment and direct question survey, for example, Coppock (2017) did not find evidence of “shy” Trump voters. In contrast to Brownback and Novotny (2018), Coppock found that the percentage of respondents who supported Trump was actually higher in the direct question survey than in the list experiment. Consequently, Coppock (2017) concluded that there was no evidence of “shy” Trump supporters in the 2016 presidential election. Prosser and Mellon (2018) also point out that sampling error and problems with weighting could be more to blame for problems with pre-election polls than social desirability bias. Sampling error is problematic because it means that segments of the electorate are oversampled or undersampled (Dillman, Smyth, and Christin 2014, 57). When this occurs, the sample is not representative of the true population (Dillman, Smyth, and Christian 2014, 57). Researchers can try to correct for sampling error by weighting the data, which aims to make the data more representative of the population of interest (Dillman, Smyth, and Christian 2014, 58). However, weighting can also introduce sampling error (Dillman, Smyth, and Christian 2014, 58). In short, Prosser and Mellon (2018) contend that social desirability bias alone would not account for differences between pre-election polls and the outcome of the 2016 U.S. presidential election.

Reluctance to Express Vote Choice and Survey Mode

Another aspect of the debate over social desirability bias involves the survey mode, or how the survey was administered. Dillman, Smyth, and Christian (2014) identify four main

Reluctance to Express Vote Choice among Ohioans during the 2016 U.S. Presidential Election

survey modes: mail or written, phone, face-to-face, and online. Mail and online surveys are self-administered whereas phone and face-to-face surveys are interviewer-administered. That is, a live person asks the respondent a list of structured questions over the phone or in person. Interviewer-administered surveys may be more prone to social desirability bias than selfadministered surveys because respondents may be less likely to state a controversial opinion to a live interviewer (Dillman, Smyth, and Christian 2014; Pew Research Center 2015). For instance, a Pew Research Center (2015) study tested the mode effect on several different social issues and found that respondents gave more socially desirable responses in the interviewer-administered survey than in the self-administered survey. The study also concluded that respondents are more likely to be honest in self-administered surveys (Pew Research Center 2015). After the 2016 U.S. presidential election, several studies compared polling results from phone surveys to online surveys to ascertain whether there may have been a mode effect in pre-election polls (see, e.g., Darling 2017, Edsall 2016). Several studies concluded that interviewer-administered surveys were more prone to social desirability bias than self-administered surveys (see, e.g., Darling 2017, Edsall 2016). For instance, Edsall (2016) found that people were more likely to support Trump’s call for a “total and complete shutdown of Muslim’s entering the United States” in online polls than in telephone polls (para. 14). This suggests that respondents may have been more reluctant to express support for Trump in intervieweradministered surveys than in self-administered surveys. In another study, respondents were asked to rate their level of comfort in disclosing their preferred presidential candidate with family, close friends, acquaintances, and telephone pollsters (Darling 2017). The study found that some Trump voters – specifically those who lived in rural areas without college degrees– were less willing to disclose their preferred presidential candidate to telephone pollsters. These results are important because they indicate that some voters who were more reluctant to express their candidate choice, suggesting some level of social desirability bias. In addition, several studies found that intervieweradministered surveys underestimated support for Trump (see, e.g., Dropp 2015, 2016; Easley 2016; Shepard 2016). Dropp (2015) found that interviewer-administered surveys underestimated support for Clinton during the Democratic primary elections, especially among respondents who were better-educated. Easley (2016) found that phone surveys underestimated support for Trump, especially among bettereducated respondents. Shepard (2016) also found that interviewer-administered surveys underestimated support for Trump. Specifically, Trump performed better in online polls among better-educated respondents and those making more than $50,000 a year, which suggests that better educated and wealthier individuals may be more prone to social desirability bias during the 2016 election than individuals with lower levels

of education and income. However, both Easley (2016) and Shepard (2016) concluded that the presence of “shy” Trump supporters in pre-election polls were too few to influence the outcome of the election. Although some studies identified mode effects (selfadministered versus interviewer-administered), others did not. On behalf of the American Association of Public Opinion Research (AAPOR), Kennedy et al. (2018) analyzed all election polls from September 1, 2016, through Election Day. To determine whether Trump supporters may have hidden their support, the authors compared levels of Trump support in live-administered polls to self-administered polls. They found no significant difference in levels of Trump support between interviewer-administered surveys and self-administered surveys. Consequently, they concluded there was little evidence in support of “shy” Trump voters. To summarize, there is conflicting evidence about the extent to which people were reluctant to express their support for Trump in public opinion polls, and whether social desirability bias may have compromised the accuracy of preelection polls. To reconcile these competing findings, this study asks: Were Trump voters more reluctant to share their vote choice than people who supported other candidates? Based on existing literature, as well as the controversial nature of Trump’s candidacy, it is hypothesized that Trump voters were more reluctant to share their vote choice. This expectation is tested using original survey data from Ohio.

Ohio as a Test Case

Since the data stem from one state, some contextual remarks are in order. First, since 1964, no presidential candidate has won the presidency without winning the state of Ohio, and only three have done so since 1860 (Kondik 2016; Sracic and Binning 2016). Trump’s victory in the 2016 election was the 14th consecutive election in which Ohio voted for the winning candidate (Tobias 2016). Second, Ohio is a swing state and a bellwether state, meaning that Ohio tends to vote for the candidate who wins the presidential election (Kondik 2016; Sracic and Binning 2016). Indeed, Trump’s support in Ohio was indicative of his support in other Midwestern states such as Pennsylvania, Wisconsin, and Michigan, which were all mustwin states for Clinton (Silver 2017). Third, although Trump won the popular vote in Ohio by about eight percentage points, pre-election polls predicted a much closer race (Federal Election Commission 2017, FiveThirtyEight 2016). Only one week before the election, for instance, Nate Silver, a wellknown statistician, predicted Trump’s chances of winning Ohio only at 60% (FiveThirtyEight 2016). Moreover, as reported in Table 1, pre-election polls suggested that the race would be very close. In fact, most pre-election polls in Ohio suggested that the race between Trump and Clinton was a statistical tie, with Green Party candidate Jill Stein garnering 0.5% to 3% of the vote and Libertarian candidate Gary Johnson winning roughly 2% to 7% of the vote.

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Table 1. Summary of Ohio Pre-Election Polls for the 2016 U.S. Presidential Election Poll

Dates Fielded

Sample Size, Mode, MOE

Percent Support Trump

Percent Support Clinton

Percent Support Johnson

Percent Support Stein

Emerson

Nov. 4-5

N=900, IVR, ±3.2%

46%

39%

CBS News/ YouGov

Nov. 2-4

N=1189, online, ±4.1%

46%

45%

Columbus Dispatch

Oct. 27 – Nov. 5

N=1151, mail, ±2.9%

47%

48%

N/A

Remington Research

Nov. 1-2

N=2,557, IVR, ±1.9%

45%

44%

N/A

Quinnipiac

Oct. 27 -Nov. 1

N=589, phone, ±4.0%

46%

41%

Trafalgar Group

Oct. 24-26

N=1150, IVR, ±2.9%

49%

44%

0.5%

CNN/ORC

Oct. 10-15

N=744, phone, ±3.5%

48%

44%

Emerson

Oct. 10-12

N=600, IVR, ±3.9%

43%

45%

Notes: This table reports results of polls conducted in Ohio in the month leading up to the 2016 U.S. presidential election. The table includes the name of the polling firm; dates the poll was in the field; sample size, survey mode, and margin of error (MOE); and the results. For survey mode, IVR denotes Interactive Voice Response, or when firms use an automated computer to ask questions instead of a live interviewer. Data were compiled from FiveThirtyEight.com and RealClearPolitics.com.

Table 2. 2016 U.S. Presidential Election Results in Ohio Candidate

Total Votes

Percent Total

Donald J. Trump

2,841,005

51.69%

Hilary Clinton

2,394,164

43.56%

Gary Johnson

174,498

3.17%

Jill Stein

46,271

0.84%

Other

40,549

0.74%

Total

5,496,487

100.00%

Notes: Data compiled from 2017 Federal Election Commission report. “Other” votes include write-in candidates.

As Table 1 shows, once the margin of error was taken into account, all pre-election polls in Ohio suggested that the race between Trump and Clinton was a statistical tie. Across eight polls, support for Trump ranged from 43% to 49% and averaged 46%. For Clinton, support ranged from 39% to 48% and averaged 44%. With the margin of errors ranging from ±1.9% in the Remington Research poll to ±4.1% in the CBS News/YouGov poll, all pre-election polls suggested that the race between Trump and Clinton would be close Although pre-election polls forecast a tight race between Trump and Clinton, Trump won Ohio by 8 percentage points (see Table 2). In fact, Ohio was the first swing, or battleground, state to be called for Trump. This result came as a surprise to many. Immediately after CNN projected Trump would win 36

Ohio, for instance, CNN’s Jake Tapper expressed disbelief that the state was called so quickly for Trump despite pre-election polls and Democrats’ confidence in winning the state’s 18 electoral votes (CNN 2016). The discrepancy between the preelection polls and the final election results suggested that voters may have been reluctant to express their support for Trump in pre-election polls.

Data and Methods

To test the proposed hypothesis, I contributed questions to an original survey instrument that were designed to understand President Trump’s victory in the battleground and bellwether state of Ohio. My “Public Interest Research” course at Baldwin Wallace University (BW) designed the survey at

Reluctance to Express Vote Choice among Ohioans during the 2016 U.S. Presidential Election

the behest of editors and reporters at cleveland.com, a regional newspaper serving the Northeast region of Ohio.

Survey Administration

After my “Public Interest Research” class drafted the survey instrument, we programed the survey using Qualtrics, a subscription-based software platform that allows users to create and distribute online surveys. The final instrument was administered in consultation with Baldwin Wallace’s Community Research Institute through the online panel Qualtrics curated between February 24, 2017, and March 8, 2017 (N = 1,019). Likely voters were classified as people who voted in the 2012 U.S. presidential election, and who were “absolutely certain” they were registered to vote at their current address. The quotas for age and gender were based on data from the 2014 American Community Survey (ACS) for Ohio. Respondents were selected to participate from an online panel with quotas in place for gender (51% female) and age (24% 18-34, 39% 35-54, 18.5% 55-64, 18.4% 65 and older) based on data from the 2014 ACS for Ohio. Compared to the 2014 ACS data, respondents in this sample were better educated. For this reason, the final data were weighted by education to match population parameters from the 2014 ACS.

Dependent Variable

My dependent variable is reluctance to share vote choice. To measure this variable, I used an adaptation of the item count technique to mask the true intent of the question (i.e., whether people were reluctant to share their vote choice). Other researchers interested in social desirability have utilized this approach, and they have found that it encourages respondents to answer more truthfully than if they are asked a separate question about vote intent (Brownback and Novotony 2018; Holbrook and Krosnick 2010). Specifically, respondents were asked to select any of five randomized statements with which they agreed. These statements included: (1) “I think presidential campaigns are too costly”; (2) “I think that the U.S. should increase the number of Immigration and Customs Enforcement (ICE) Officers”; (3) “I think that the U.S. should produce more oil and natural gas”; (4) “I think that the U.S. should produce more renewable energy (wind, solar, etc.)”; and (5) “During the 2016 presidential election, I was reluctant to tell other people which candidate I was voting for.” Although the question included five statements, I was interested only in responses to the statement about reluctance to share vote choice (#5), and I recoded this variable as 0 (“not reluctant”) and 1 (“reluctant”). Descriptive statistics show that about 24.92% of respondents were reluctant to share their vote choice (M = 0.25, SD = 0.43).

Independent Variable

My main independent variable is “vote choice” because I hypothesized that Trump voters were more reluctant to share their vote choice for Trump. To measure vote choice, I

asked respondents for whom they voted for in the 2016 U.S. presidential election. Options included both major party candidates (i.e., Hillary Clinton and Donald Trump), thirdparty candidates (i.e., Gary Johnson and Jill Stein), and “other.” Descriptive statistics show that about 41.13% of respondents voted for Clinton, about 49.40% voted for Trump, about 4.93% voted for Johnson, about 1.00% voted for Stein, and about 3.55% selected “other.” Using these data, I created five indicator, or dummy, variables (i.e., k - 1) to compare Clinton voters to Trump voters (M = 0.41, SD = 0.49), Johnson voters to Trump voters (M = 0.05, SD = 0.22), Stein voters to Trump voters (M = 0.01, SD = 0.10), and people who voted for someone other than the four main candidates to Trump voters (M = 0.04, SD = 0.19). Each of these five variables allows me to compare whether people who voted for Clinton (coded 1), Johnson (coded 1), Stein (coded 1), or another candidate (coded 1) were less reluctant to express their vote choice than people who voted for Trump (coded 0), respectively.

Control Variables

I also controlled for other variables that may explain one’s reluctance to share vote choice. These variables include gender, age, education, and income. I controlled for gender due to the controversial nature of Trump’s comments toward women. In addition, women are less likely than men to express an opinion in public opinion polls (Burns, Schlozman, and Verba 2001; Coffé and Bolzendahl 2010; Graham 2016; PerryUndem 2017; Verba, Schlozman, and Brady 1995). Gender is a dichotomous variable coded 1 for female (51.8% female) and 0 for male. I controlled for age because research shows that younger voters may be reluctant to share their vote choice. Compared to older voters, younger voters tend to feel less enthusiastic about the major party candidates, feel more dissatisfied with the political system, and tend to engage in self-monitoring more often (Benedict-Nelson 2012; Claassen and Ryan 2016; Dalton 2016; Pasek, Kenski, Romer, and Jamieson 2006). Age was measured as a categorical variable. The categories were as follows: 18 to 29 years (20.6%), 30 to 44 years (22.7%), 45 to 64 years (35.8%), and 65 years or older (20.9%). Using this variable, I created four dummy variables (i.e., k-1) with age 65 years and older as the baseline category. I also controlled for education and income because people who are better educated and/or wealthier may be more likely to give socially desirable responses to public opinion polls (Dropp 2015). To measure education, respondents were asked to indicate the highest level of education completed, which ranged from “less than high school” (coded 1) to “postgraduate degree” (coded 6) (Mean = 3.63, median = “some college”, SD=1.49). Respondents were also asked to indicate their annual household income. The scale ranged from $0 $25,000” (coded 1) to $150,001 or more (coded 7) (Mean = 2.83, median = $50,001 - $75,000, SD = 1.49).

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Analytic Strategy

To test my expectations, I conducted bivariate and multivariate analyses. Specifically, I conducted Chi-square tests because my dependent variable and my main independent variables are categorical (Pollock 2016). Next, I estimated a logistic regression model, which is the most appropriate model for a dichotomous or binary dependent variable (Pollock 2016), to predict which groups were reluctant to express their vote choice during the 2016 U.S. presidential election (0 = “not reluctant”, 1 = “reluctant”).

Results Bivariate Analysis

I begin with bivariate statistics, in which I outline the percentage of respondents who were reluctant to share their vote choice during the 2016 U.S. presidential election by vote choice, gender, age, education, and income. As Table 3 shows, Trump supporters were no more reluctant than other voters to express their vote choice (χ 2 = 3.79, p = 0.431). Instead, Libertarian candidate Gary Johnson’s supporters were the

Table 3. Percent Reluctant to Share Vote Choice by Vote Choice, Gender, Age, Education, and Income Percent Reluctant

χ2 = 3.79, p = 0.431

Vote Choice Vote Clinton

24.63%

Vote Trump

24.08%

Vote Johnson

35.81%

Vote Stein

19.56%

Vote Other

18.70% χ 2 = 20.56, p = 0.000

Gender Female

30.84%

Male

18.55% χ 2 = 25.88, p = 0.000

Age 18 to 29

38.10%

30 to 44

24.03%

45 to 64

21.10%

65 and older

19.50% χ 2 =10.12, p = 0.174

Education Less than HS

14.29%

HS Diploma

21.27%

Some college

25.10%

2-year degree

21.15%

4-year degree

27.70%

Postgraduate degree

32.90% χ 2 = 5.80, p = 0.431

Income

Test Statistic

$0 - $25,000

19.16%

$25,001 - $50,000

24.56%

$50,001 - $75,000

25.56%

$75,001 - $100,000

27.77%

$100,001 - $125,000

28.33%

$125,001 - $150,000

31.97%

$150,001 and up

30.17%

Reluctance to Express Vote Choice among Ohioans during the 2016 U.S. Presidential Election

most reluctant (about 35.81%), followed by Clinton voters (about 24.63%), Trump voters (about 24.08%), Stein voters (about 19.56%), and voters who voted for another candidate (18.70%). The results are displayed graphically in Figure 1. These findings demonstrate that people who supported Johnson were among the most reluctant to share their vote choice (i.e., not Trump voters), perhaps because their support signaled a defection from the Republican Party. In addition, perhaps they knew that a vote for a conservative third-party candidate would hurt Trump and help Clinton (Shirky 2016). Although there was not a strong relationship between reluctance and vote choice, significant relationships emerged for gender and age. As Table 3 shows, roughly 30.84% of female voters were reluctant to share their vote choice compared to only about 18.55% of male voters (χ 2 = 20.56, p = .000). In addition, younger voters were significantly more reluctant than older voters to express their vote choice (χ 2 = 25.88, p = .000; see Table 3). Among voters ages 18-to-29 years, about 38.10% were reluctant to share their vote choice, compared to about 24.03% of those 30-to-44 years-old, about 21.10% of those 45-to-64 years-old, and about 19.50% of those ages 65 years and older. In other words, people ages 18to-29 years were about 18.60 percentage points more likely to say they were reluctant to express their vote choice than people ages 65 years and above. Third, as people’s level of educational attainment increased, so did their reluctance to share their vote choice (see Table 3). As Table 3 shows, people with a post-graduate degree were about 18.61 percentage points more reluctant to express Figure 1: Reluctance to Share Vote Choice by Choice of Candidate

Percent Reluctant to Share Vote Choice

90 81.26

80.44

75.92

75.37

70 64.19

60 50 40

25.81

30 24.63

their vote choice than people with less than a high school degree. However, differences by level of educational attainment were not statistically distinct from zero in the bivariate analysis (χ 2 =10.12, p = 0.174). Finally, wealthier people were more reluctant to express their vote choice, but this result was not significant in the bivariate analysis (χ 2 = 5.80, p = 0.431). As Table 3 shows, about 30.17% of people who earned more than $150,001 per year or more were reluctant to share their vote choice compared to about 19.16% of those with an income between $0 and $25,000 – a difference of about 11.01 percentage points. To summarize, the descriptive and bivariate statistics showed that those who were the most reluctant to share their vote choice were Johnson voters, females, 18-to-29-year-olds, those with a post-graduate degree, and people who earned $125,001 to $150,000. However, significant relationships emerged only for gender and age.

Multivariate Analysis

Next, I turn to multivariate analysis to examine whether Trump voters were more reluctant than other voters to share their vote choice, holding all else constant. Table 4 compares Clinton voters, Johnson voters, Stein voters, and other voters to people who voted for Trump with controls in place for gender, age, education, and income. Compared to Trump voters, Clinton voters were not more reluctant to share their vote choice (β = -0.131, p = 0.453). Neither were Johnson voters (β = 0.360, p = 0.306), Stein voters (β = -0.546, p = 0.538), nor people who voted for write-in candidates (β = -0.685, p = 0.158). In short, the data do not support my hypothesis; Trump voters were not more or less reluctant than other voters to share their vote choice. However, some interesting results emerge among the control variables. First, women were significantly more reluctant than men to express their preference (β = 0.636, p = 0.000). In addition, younger people ages 18-to-29 were more reluctant than people ages 65 years and older to share their vote choice (β = 0.843, p = 0.001). Third, people with higher levels of educational attainment were more reluctant to share their vote choice than people with lower levels of educational attainment (β = 0.143, p = 0.018). Finally, wealthier individuals were slightly more reluctant to tell others for whom they were voting (β = 0.103, p = 0.074), but this relationship failed to achieve significance at the p < .05 threshold.

24.08 19.56

18.74

DISCUSSION AND CONCLUSION

10 0 Clinton

Trump

Johnson

Stein

Presidential Candidate Reluctant

Not Reluctant

Other

Since Donald Trump won the 2016 U.S. presidential election, scholars and pollsters alike have wondered whether public opinion polls underestimated the electorate’s support for Trump. This study examined whether Ohioans who voted for Trump were more reluctant than people who voted for other candidates to express their vote choice. On average, pre-election polls in Ohio showed that 46.25% of voters supported Trump

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Table 4. Logistic Regression Model Predicting Reluctance to Share Vote Choice Coefficient

Standard Error

p-value

Vote Clinton (=1)

-0.131

(0.174)

0.453

Vote Johnson (=1)

0.360

(0.352)

0.306

Vote Stein (=1)

-0.546

(0.887)

0.538

Vote Other (=1)

-0.685

(0.485)

0.158

Female (=1)

0.636***

(0.178)

0.000

18-29 years (=1)

0.843***

(0.247)

0.001

30-44 years (=1)

0.271

(0.248)

0.274

45-64 years (=1)

0.209

(0.235)

0.373

Education

0.143*

(0.060)

0.018

Income

0.103+

(0.058)

0.074

-3.203***

(0.443)

0.000

Constant

Observations (N)

904

Likelihood-ratio χ2(10) = 47.82*** Pseudo R2 = 0.048 Notes: Model predicts the likelihood that respondents were reluctant to share their vote choice during the 2016 U.S. presidential election. The baseline category for the vote choice dummy variables is “Vote Trump.” The baseline category for age is 65 years or older. *** p < 0.001, ** p < 0.01, * p < 0.05, + p < 0.10

and 43.75% of voters supported Clinton. However, Trump won Ohio by about eight percentage points. This discrepancy, in addition to Trump’s controversial statements during the election campaign, led me to hypothesize that people who voted for Trump were more reluctant to express their true preference than people who supported other candidates. However, the data did not support this hypothesis. Descriptive statistics revealed that people who supported Libertarian candidate, Gary Johnson, were the most reluctant to share their vote choice. Johnson voters may have been the most reluctant to share their vote choice for two main reasons. First, votes for third-party candidates, or protest votes, are not effective in plurality electoral systems. Although protest votes have the potential to disrupt an election, such as during the 1992 U.S. presidential election with independent candidate Ross Perot, protest votes tend to be futile, and they are often perceived as “throw-away” votes (Shirky 2016). Second, votes for third-party candidates tend to hurt the major party that is closest to them on the left-right ideological spectrum (Downs 1957; Shirky 2016). In this instance, a vote for Johnson would have hurt Republican nominee Donald Trump and would have helped Democratic nominee Hillary Clinton. For these reasons, Johnson voters may have been reluctant to share their vote choice. Although descriptive statistics showed that Johnson supporters were among the most reluctant to express their 40

vote choice, the multivariate analysis showed that Johnson voters were not more reluctant than Trump voters to express their vote choice. In fact, people who supported Clinton, Johnson, Stein, or other candidates, were no more reluctant than people who supported Trump to share their vote choice. As the descriptive statistics show, Clinton and Trump voters were equally reluctant to express their vote choice at 24.63% and 24.08%, respectively. This may be due to the unpopularity of both Trump and Clinton (Easley 2016; Gabriel 2016). In American politics, people often talk about casting their vote for the “lesser of two evils,” but in this election, both major-party candidates had historically low favorability ratings and were equally disliked (Easley 2016). Although Trump voters were not more reluctant than other voters to share their vote choice, women were more reluctant than men to share their vote choice, as were younger, better educated, and wealthier individuals. The descriptive, bivariate, and multivariate analyses show that women were significantly more reluctant than men to express their vote choice. Women may have been more reluctant to express their vote preference for one of two reasons. First, studies suggest that women may be more reluctant than men to express political opinions in general (Burns, Schlozman, and Verba 2001; Coffé and Bolzendahl 2010; Graham 2016; Verba, Schlozman, and Brady 1995). Second, women who planned to vote for Trump may have been reluctant to voice their support

Reluctance to Express Vote Choice among Ohioans during the 2016 U.S. Presidential Election

for his candidacy given the degrading comments he made about women throughout the election. Indeed, a majority of women viewed the comments Trump made during the campaign as inappropriate, which may have prevented them from disclosing their intent to vote for him (PerryUndem 2017). Similarly, women who planned to vote for Clinton may not have felt enthusiastic about their vote choice, as Clinton was an unpopular candidate (Gabriel 2016). The results also demonstrated that people ages 18to-29 years were significantly more reluctant to express their vote choice than people ages 65 years and above. This finding is consistent with other studies, which have found that younger individuals were more reluctant to share their support for Clinton (Claassen and Ryan 2016). Younger voters who supported Trump may also have been more reluctant to express their preference because they did not want to share an opinion that could be perceived as controversial. As Galston and Hendrickson (2016) found, younger people voted for Trump by greater margins than pre-election polls predicted. Younger voters may have been more reluctant than older voters to express their vote choice because they were not enthusiastic about any of the candidates in the general election (Blake 2016; Stein 2016). In other words, the reluctance gap between the youngest and oldest voters may have been non-existent had Bernie Sanders been the Democratic nominee, especially considering only 18% of young Clinton voters were enthusiastic about her candidacy (Galston and Hendrickson 2016). Finally, younger people’s dissatisfaction with the electoral process may have made them feel less willing to discuss politics (i.e., share their vote choice) with others (Benedict-Nelson 2012; Dalton 2016; Galston and Hendrickson 2016; Pasek, Kenski, Romer, and Jamieson 2006). The multivariate analysis also revealed that people with higher levels of educational attainment were significantly more reluctant to share their vote choice than people with lower levels of educational attainment. This finding is consistent with other studies (e.g., Dropp 2015, 2016; Easley 2016; Shepard 2016), in which researchers found that Trump polled better among better-educated individuals in online surveys and polled worse in live-interviewer surveys. However, it is not clear whether higher education makes people more immune to social desirability bias, or if higher education makes people better at concealing opinions or views that they perceive to be unpopular (Heerwig 2009). More research on this point is needed. Finally, wealthier individuals were slightly more reluctant to share their vote choice than people who earned less money. This finding is consistent with other research on social desirability bias and household income. Pre-election polls showed that wealthier voters were more reluctant to express their support for Trump during the general election (Dropp 2016; Easley 2016; Shepard 2016). Studies also identified a survey mode effect for wealthier voters; those with a higher income were more reluctant to express their support for Trump

in phone surveys than they were in online surveys (Dropp 2016; Easley 2016; Shepard 2016). However, it is unclear why wealthier individuals were more reluctant to share their vote choice. More research is needed on this point as well. These findings are important because they add to a growing body of literature on the possibility of social desirability bias in pre-election polls during the 2016 U.S. presidential election. Although some studies have found little evidence of social desirability bias in pre-election polls for the 2016 U.S. presidential election (e.g., Coppock 2017; Enten 2016; Kennedy et al. 2017; Prosser and Mellon 2018), other studies have found evidence of social desirability effects (e.g., Brownback and Novotny 2018; Claassen and Ryan 2016; Dropp 2015, 2016; Easley 2016; Enns, Lagodny, and Schuldt 2017; Enns and Schuldt 2016; Galston and Hendrickson 2016; Klar, Weber, and Krupnikov 2016). This study suggests that certain segments of the electorate – including women, and people who are younger, better educated, and wealthier – are more prone to social desirability bias than others.

Limitations and Future Research

Of course, this study is not without limitations. First, the scope of the analysis is limited to Ohio. Although Ohio is a battleground and bellwether state (Kondik 2016; Sracic and Binning 2015), future research should examine the possibility of social desirability bias in other states where Trump won after trailing in the polls, such as Florida, Michigan, North Carolina, Wisconsin, and Pennsylvania (FiveThirtyEight 2016). Second, this study could not test for mode effects by comparing the results from an interviewer-administered poll to a self-administered poll. Future research should explore the possibility of mode effects as well by comparing survey results that were collected through different modes, such as online and with a live interviewer. Scholars should also examine whether the results of this study were specific to the 2016 U.S. presidential election, or if they represent broader trends of voters who are subject to social desirability bias. Going forward, public opinion research should focus additional attention on minimizing the possibility of social desirability bias in pre-election polls. This is important for future pre-election polling, especially in battleground states that are a “must-win” for candidates. If voters are not honest about whom they plan to vote for, there is a possibility that we will see more surprise election results in the future. n

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Shirky, Clay. 2016. “There’s No Such Thing as a Protest Vote.” Medium. https://medium.com/@cshirky/theres-no-such-thing-as-aprotest-vote-c2fdacabd704 (Accessed June 28, 2019).

Kondik, Kyle. 2016. The Bellwether: Why Ohio Picks the President. Athens, OH: Ohio University Press.

Silver, Nate. 2017. “Ohio was a Bellwether after All.” FiveThirtyEight. https://fivethirtyeight.com/features/ohio-was-a-bellwether-after-all/ (Accessed June 28, 2019).

Levin, Blair. 2008. “What Bradley Effect?” The New York Times. https://www.nytimes.com/2008/10/20/opinion/20levin.html (Accessed June 25, 2019). Mercer, Andrew, Claudia Deane, and Kyley McGeeney. 2016. “Why 2016 Election Polls Missed their Mark.” Pew Research Center. http://www.pewresearch.org/fact-tank/2016/11/09/why-2016election-polls-missed-their-mark/ (Accessed June 28, 2019). Meyers, David Ross. 2016. “A Message for my Fellow Republicans: If you Back Trump you will not be Trusted Again.” Fox News. http:// www.foxnews.com/opinion/2016/05/03/any-republican-whothinks-its-better-to-elect-trump-than-hillary-needs-their-headexamined.html (Accessed June 28, 2019).

Stein, Jeff. 2016. “Two Pretty Understandable Reasons so Few Young Voters are Excited about Hillary Clinton.” Vox. https://www.vox. com/policy-and-politics/2016/10/5/13148042/hillary-clintonyoung-voters (Accessed June 28, 2019). Sracic, Paul, and William Binning. 2016. Ohio Government and Politics. CQ Press. Tamman, Maurice. 2016. “Clinton has 90 percent Chance of Winning: Reuters/Ipsos States of the Nation.” Reuters. https:// www.reuters.com/article/us-usa-election-poll/clinton-has-90percent-chance-of-winning-reuters-ipsos-states-of-the-nationidUSKBN1322J1 (Accessed June 28, 2019).

Pi Sigma Alpha Undergraduate Journal of Politics Time Staff. 2015. “Here’s Donald Trump’s Presidential Announcement Speech.” Time. http://time.com/3923128/ donald-trump-announcement-speech/ (Accessed June 28, 2019). Tobias, Andrew J. 2016. “Ohio again Picks a Winner in Donald Trump, but Bellwether Status not Unscathed.” cleveland.com. https://www.cleveland.com/open/index.ssf/2016/11/ohio_ again_picks_a_winner_in_d.html (Accessed June 28, 2019). United States Federal Election Commission. 2017. Official 2016 Presidential General Election Results. https://transition.fec.gov/ pubrec/fe2016/2016presgeresults.pdf (Accessed June 28, 2019). Verba, Sidney, Kay Lehman Schlozman, and Henry E. Brady. 1995. Voice and Equality: Civic Voluntarism in American Politics. Cambridge, Massachusetts: Harvard University Press. Vitali, Ali. 2016. “In His words: Donald Trump on the Muslim Ban, Deportations.” NBC News. https://www.nbcnews.com/ politics/2016-election/his-words-donald-trump-muslim-bandeportations-n599901 (Accessed June 28, 2019). Wright, Fred A., and Alec A. Wright. 2018. “How Surprising was Trump’s Victory? Evaluations of the 2016 U.S. Presidential Election and a New Poll Aggregation Model.” Electoral Studies 54:81-89. Zezima, Katie. 2016. “Trump on Immigration: There are ‘Bad Hombres’ in the United States.” The Washington Post. https:// www.washingtonpost.com/news/post-politics/wp/2016/10/19/ trump-on-immigration-there-are-bad-hombres-in-the-unitedstates/?utm_term=.6169c7b8f227 (Accessed June 25, 2019). Zurcher, Anthony. 2016. “U.S. Election 2016 Results: Five reasons Donald Trump Won.” BBC News. https://www.bbc.com/news/ election-us-2016-37918303 (Accessed June 28, 2019).

NOTES 1. The Department of Politics and Global Citizenship at Baldwin Wallace offers “Public Interest Research” each spring to fulfill the university’s experiential learning requirement. As a part of this course, students complete an original research project on behalf of an external organization or agency. In spring 2018, our class partnered with cleveland.com, a major daily newspaper in Ohio, to conduct a post-election survey of Ohioans. 2. These figures increase my confidence in the data because they are within three points of the actual election results in Ohio.

Analyzing the Potency of Lawfare in the Israeli-Palestinian Conflict

Analyzing the Potency of Lawfare in the Israeli-Palestinian Conflict Jack Hostager, University of Pennsylvania Lawfare, “the strategy of using – or misusing – law as a substitute for traditional military means to achieve an operational objective,” is an increasingly important aspect of the Israeli-Palestinian conflict. But how effective, or potent, is lawfare compared to traditional kinetic warfare? This paper proposes a framework for evaluating the potency of lawfare in relation to warfare in terms of the traditional levels of war: tactical, operational, and strategic. Several instances of lawfare are analyzed in the Israeli-Palestinian conflict, including universal jurisdiction cases against Israeli officials in European courts and the targeting of Hamas financing networks in US courts. It is argued that Israel tends to be successful at lawfare at the tactical and operational level by winning cases and using lawfare to achieve its operational objectives, but it struggles to manage the unintended strategic implications of lawfare. In this way, lawfare is at least as potent as the warfare it replaces or supplements in the Israeli-Palestinian conflict, but not always in the way its wielder intends.

INTRODUCTION ecisive military victories have become increasingly rare since the end of the Cold War. (Toft 2010, 14). Nowhere is this more apparent than in the Israeli-Palestinian conflict, where at first glance it seems Israel should have decisively overtaken the Palestinians long ago. The Israeli Defense Forces (IDF) is one of the most technologically sophisticated militaries in the world, with an annual budget of $15 billion, 176,500 active duty personnel, and an air force of almost 700 aircraft (Bender and Rosen 2014). The Palestinian Authority (PA), by contrast, has no standing army and relies on Israel for external security (Israel Ministry of Foreign Affairs 1995). The Israeli economy has a Gross Domestic Product (GDP) of $351 billion, while the Palestinian territories have a GDP of $14 billion and are largely dependent on Israel for key imports (The World Bank 2017). Israel is also unified under a modern democratic government, while Palestinian political authority is split between the Palestinian Authority in the West Bank and internationallyostracized Hamas in the Gaza Strip. Both Palestinian governments lack strong institutions, and many social services in the Palestinian territories are delivered by international NonGovernmental Organizations (NGOs). Given this massive disparity in military and economic resources, why did the conflict not end years ago with Israel as the uncontested victor? The full answer to this question is complicated, multifaceted and beyond the scope of this paper, involving regional power dynamics in the Middle East, historical support for a negotiated two-state solution by Israel’s allies, and divisions within Israel over what to do about the Palestinian problem. But it is at least partly related to the fact that military and economic strength are rarely sufficient to cause victory in political conflict. While Israel dwarfs the

Palestinians in terms of population (The World Bank 2018), territory (Food and Agriculture Organization 2008, 215, 279), and economic and military resources (Bender and Rosen 2014; Israel Ministry of Foreign Affairs 1995; The World Bank 2017) the Palestinians retain cultural and social resources, as well as diplomatic and legal tools, that are significant enough to challenge Israel and prevent it from achieving a decisive victory. One of the most fascinating of these tools is “lawfare.” The term lawfare, the amalgamation of the words “law” and “warfare”, was coined by Major General Charles Dunlap of the U.S. Air Force Judge Advocate General’s Corps as “the strategy of using – or misusing – law as a substitute for traditional military means to achieve a warfighting objective” (Dunlap 2011, 315). Lawfare is a relatively new field of study, as the existing literature on lawfare has largely sought to document the use of lawfare by states like Israel and China (Hsiao 2016) and NGOs focused on human rights and environmental issues (Konkes 2018). Other scholars have considered the prospects for using lawfare to fight climate change (Clegg 2018)it was clear that ClientEarth would need to work internationally to achieve its ambitions. Tony Long, a Brussels-based environmentalist, was director of the European Policy Office of WWF (the European equivalent of the United States’ World Wildlife Fund and ISIS (Kotzambasis 2018). A small number of legal ethicists have analyzed whether lawfare is a positive and appropriate use of national and international law (Fisher and Stefan 2016). However, few scholars have considered a basic question: how potent is lawfare when measured against the kinetic warfare it replaces? This paper sets out to answer that question in the context of the Israeli-Palestinian conflict. Space constraints prevent an analysis of each of the hundreds of instances of lawfare in the conflict, so a case-study analysis of several of the most

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potent examples of lawfare in the conflict is used to evaluate its effectiveness when compared to traditional kinetic warfare. It is argued that lawfare is indeed a potent weapon in the conflict, but its implications are vastly different for Israel and Palestine. While Israel has proven to be highly effective at using lawfare offensively and defending against individual cases Palestinian lawfare, it has not been able to use lawfare to systematically undermine its adversaries. By contrast, Palestinian lawfare is often unsuccessful in the courtroom, but it has prompted systematic changes in the way Israel deploys force on the kinetic battlefield. The strategic success of Palestinian lawfare, combined with the unintended consequences of Israeli lawfare, has made lawfare one of the most effective tools with which the Palestinians can challenge Israel despite their military disadvantage. This paper will begin with a conceptual overview of the concept of lawfare and its relationship to kinetic warfare. I will propose a novel way of conceptualizing lawfare through the lens of the three levels of traditional war. Then several case studies will be analyzed involving lawfare against Israel and Israel deploying lawfare against its adversaries. Then the consequences of this lawfare will be examined for the various parties in the conflict and consider whether lawfare can tilt the balance of power in the conflict as effectively as kinetic warfare.

Conceptual Framework

Charles Dunlap, then a colonel in the U.S. Air Force Judge Advocate General’s Corps, first described “lawfare” in a 2001 essay as “a method of warfare where law is used as a means of realizing a military objective” (Dunlap 2001, 4). In subsequent essays, he refined his definition as “the strategy of using – or misusing – law as a substitute for traditional military means to achieve a warfighting objective” (Dunlap 2011). According to Dunlap (2017, 9), lawfare provides “an easily understood ‘bumper sticker’ phrasing for how belligerents… are attempting to use law as a form of ‘asymmetric’ warfare. Lawfare has been around since there was first law and war, but there has been an increasing amount of lawfare around the world (and particularly in the Israeli-Palestinian conflict) since the 1990s. There are several reasons for the rise of lawfare: the increasingly asymmetric nature of modern conflict creates incentives for less powerful states to seek more favorable “battlescapes” on which to challenge more powerful opponents; the Internet and mobile technology have made evidence of violations of international law is easier to document and share than ever before; the number of human rights and legal advocacy NGOs to pursue lawfare cases has grown exponentially (Kittrie 2016, 47); and the international system is an increasingly law-rich environment, creating what one international lawyer dubs “an incentive for legal creativity— seeking to frame issues in innovative ways and taking advantage of legal rules that help your side” (Trachtman 2016, 270). A textbook example of lawfare was Israel’s use of law to stop the “Gaza Freedom Flotilla” from delivering aid and 46

other supplies to Gaza in violation of Israel’s naval blockade. The first Gaza flotilla set sail from Turkey in 2010, and as it approached Gaza Israeli Special Forces forcibly boarded each ship in the flotilla in international waters and forced it to turn around. The operation stopped the flotilla, but by the time it was over nine passengers were killed and dozens of others were injured, leading to international outcry and a UN investigation that concluded Israel used “excessive and unreasonable” force (Palmer 2011, 4). When the flotilla organizers announced they would launch another flotilla from Greece in June 2011, Israel was anxious to avoid a repeat of the 2010 operation. The government enlisted the help of Israeli legal NGO Shurat HaDin, which sent letters to the ships’ insurers and the provider of the ships’ navigation equipment threatening legal action in U.S. court for “knowingly providing material support or resources to a foreign terrorist organization” if they did not cancel services to ships in the flotilla (Kittrie 2016, 314). Shurat HaDin also filed regulatory complaints against the ships in Greece, which the Greek Coast Guard was obliged to investigate. Several of the ships’ insurers canceled their insurance coverage, and a number of ships were ordered not to sail for regulatory violations. Ultimately at least 14 ships in the flotilla were prevented from sailing and the captain of at least one ship was arrested for sailing without permission. The flotilla fell apart largely due to Shurat HaDin’s legal maneuvers. Israel stopped the flotilla with the same effectiveness, yet none of the risks, of the botched 2010 raid (Kittrie 2016, 312–18). This example highlights many of the important aspects of lawfare: it directly replaced or supplemented a military operation, it consisted a public/private partnership between an NGO and a government, and it involved an amalgamation of jurisdictions to bring legal challenges where they would be most effective. The Gaza Flotilla example above clearly fits this description of lawfare, but other examples are less clear cut. For instance, is the Palestinian Authority successfully campaigning for non-member observer status in the U.N. General Assembly an example of lawfare? Some scholars treat it as such, arguing that it advanced Palestine’s claim to statehood without having to defeat Israel on the kinetic battlefield (Herzberg 2010; Kittrie 2016, 13). But Finkelstein notes: “if any use of law by a state to pursue national interests counts as lawfare, the line between international diplomacy and the military aims that lawfare is supposed to be advancing becomes effaced” (Finkelstein 2017). For “lawfare” to mean something, it must be limited only to using law to achieve a “warfighting objective.” More precisely, it cannot be any legal tool used to achieve the political goals of an international actor or any legal instrument used during warfare in advance of the broader strategic objectives for which a war is fought. It can only be a legal tool that directly substitutes or augments a military operation. The first major English language book on lawfare was published in 2018 by Kittrie. His book catalogs a wide range

Analyzing the Potency of Lawfare in the Israeli-Palestinian Conflict

of case studies of lawfare across the world to evaluate “lawfare’s current state and future prospects” (Kittrie 2016, 10). Kittrie (2016, 8) defines lawfare by two standards: 1) an action that uses law to create an effect similar to an outcome traditionally achieved through military action, and 2) the motivation for such an action must be to weaken or destroy an adversary. He groups lawfare into two categories: “instrumental lawfare” is the use of legal tools to replace conventional military action (for example, the Gaza Flotilla case above), and “complianceleverage disparity lawfare” is “exploiting the laws of war on the kinetic battlefield to gain an advantage over an adversary on whom those laws have a greater effect” (Kittrie 2016, 11). For example, Hamas illegally operated its military headquarters inside a wing of the Shifa hospital in Gaza during the 2009 Gaza War, predicting correctly that Israel would not risk international criticism and legal sanctions if they attacked the hospital (Kittrie 2016, 285). Lawfare can be exercised at three levels: in domestic courts (in this case, the Israeli court system), international courts (specifically the International Court of Justice and the International Criminal Court, as well as various other international bodies), and in foreign domestic courts. Lawfare in foreign domestic courts is either undertaken by a national of that country claiming damages (for example, families of U.S. citizens killed by Hamas suing organizations that funded Hamas in U.S. court) or under the principle of universal jurisdiction, which stipulates that a state may claim criminal jurisdiction over certain crimes committed beyond its borders, regardless of the prosecuting state’s relationship to the parties involved (Nicolaou-Garcia 2009, 1). The principle of universal jurisdiction was developed after the Holocaust on the premise that some crimes are of “such exceptional gravity that they affect the fundamental interests of the international community as a whole” (Macedo 2001, 23). Crimes subject to universal jurisdiction generally include war crimes, genocide, torture, and crimes against humanity (Macedo 2001, 29). In the U.K. for example, universal jurisdiction applies to the Geneva Conventions governing the international law of armed conflict, including the protection of civilian populations in times of war (Geneva Convention IV 1949). Kittrie (2016) devotes almost half of his book to lawfare in the Israeli-Palestinian conflict. He characterizes the Israeli-Palestinian conflict a “lawfare laboratory” and catalogs examples of lawfare by the Palestinian Authority, Palestinian NGOs, Hamas, and Israel. The Palestinian Authority wages lawfare by joining international organizations and pressing for ICC prosecutions, while Palestinian NGOs and their allies focus on filing legal challenges against Israel, Israeli military officers, and companies that do business with Israel in foreign domestic courts. Hamas carries out a different form of lawfare focused on inducing the Israeli Defense Forces (IDF) to violate laws of war, and Israel engages in offensive lawfare focused on cutting off funding to Hamas and using relationships with allies to shape international law and foreign laws to their

advantage. Kittrie’s (2016) central takeaway is that lawfare is shaping the Israeli-Palestinian conflict and is likely to expand as time goes on. While Kittrie’s (2016) book is a vital contribution to lawfare scholarship, the author necessarily leaves open many questions. This paper seeks to build on Kittrie’s (2016) groundbreaking research and analyze the actual effectiveness of lawfare compared to the kinetic warfare it supplements or replaces.

Framing Lawfare within the Three Levels of War

In order to analyze the potency of lawfare as compared to conventional warfare, it is necessary to articulate a framework through which the potency of each can be analyzed. More precisely, this paper aims to compare the consequences of lawfare and warfare. The most appropriate framework for this is the three levels of war. Military leaders have long recognized the value of separating war into levels, for the strategic thinking senior military leaders use to plan war strategy are different from the tactical skills infantrymen use to fight in the heat of combat (Franz 1983, 3-4). The first level of war is strategic, which relates to defining national interests and determining national policy. Clausewitz ([1832] 1976, 86-87) observed in his seminal work On War that “when whole communities go to war… the reason always lies in some political situation, and the occasion is always due to some political object.” He goes on to describe war as “a true political instrument, a continuation of political intercourse, carried on with other means” (Clausewitz [1832] 1976, 87). The strategic level involves determining an actor’s broader “political motive,” then planning which tools or combination of tools – from political pressure up to nuclear war – an actor will use to advance its interests (Sakala 1997). It addresses why an actor fights (U.S. Air Force 2015). In the case of the 2010 Gaza Flotilla, for example, Israel’s strategic objective was to destroy Hamas’ ability to threaten Israel. The second level is operational, which is “concerned with employing military forces in the theater of operations” (Sakala 1997, 2). After an actor determines its strategic interest and decides warfare is its preferred way of achieving it, the operational level involves employing “military forces in a series of related military operations to accomplish a common objective in a given time and space” (Sakala 1997, 2). The operational level exists between strategy and individual battles with an enemy, with a focus on coordinating large units in a military campaign. According to the Air Force Basic Doctrine Manual, the operational level involves determining “what courses of action, in what order, for what duration, and with what resources (U.S. Air Force 2015, 45). In the 2010 Gaza Flotilla case, the “theater of operations” was the Gaza Coast, and Israel’s operational objective was to uphold the general blockade of the Gaza Strip. Operational decisionmaking involved developing a plan to patrol the Gaza coast, anticipating who might attempt to breach the blockade and

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what means they might use, and planning what forces are necessary to counter such an anticipated breach. Finally, the tactical level “deals in the details of prosecuting engagements and are extremely sensitive to the changing environment of the battlefield” (Sakala 1997). It involves decisions about how to win a given firefight or drive an enemy from a particular position. In the case of the 2010 Gaza Flotilla raid, the tactical objective was to stop the 2010 flotilla from reaching Gaza, and the tactical level involved decisions about where to intercept the flotilla and what weapons to use against it. Similarly, when Israel chose lawfare as its weapon to stop the 2011 flotilla, the analogous “tactical level” involved further decisions about what kind of legal action to bring and what legal arguments to make. The levels of war offer a useful framework for relating the consequences of lawfare to the consequences of warfare. In the 2011 flotilla case, lawfare achieved the same tactical objective of halting the flotilla and the same operational objective of maintaining the blockade as the 2010 military operation. However, the two operations had vastly different strategic consequences. The lawfare operation was a strategic success, depriving Hamas of resources and contributing to the broader goal of Hamas’ defeat. The military operation similarly deprived Hamas of resources and inflicted casualties on Hamas supporters, but this minor strategic benefit was far outweighed by international outcry over the incident. This outcry had important strategic consequences; it became a point of contention in Israel’s relationship with its allies and put significant pressure on Israel to use less military force. In other words, lawfare aims to achieve the same operational objective as kinetic warfare, but it does so with legal tactics instead of battlefield tactics. The nexus between lawfare and warfare is usually at either the operational level or the tactical level. This is why it is hard to see how the Palestinian Authority (PA) gaining observer status to the UN General Assembly is lawfare. This advances the PA’s strategic objective of gaining legitimacy and opening up new venues in which to challenge Israel, but the “operational objective” of gaining UN recognition does not replace or supplement an operational objective that could conceivably be realized by kinetic warfare. What sets lawfare apart from other uses of law in political conflict is that it translates legal action into the “currency” of military resources. The tactical objective in lawfare is to win the case, the operational objective is the same as the warfare it replaces, and the strategic objective remains constant whether warfare, lawfare, or some other tool is used to achieve it. Additionally, this framing highlights the ways in which lawfare can undermine the very interests it serves. Successful military operations should involve victory at the tactical, operational, and strategic levels. But it is possible for a military operation to be a tactical or operational success and still be a strategic failure, or vice-versa. For example, the U.S. won a number of key tactical victories in the Vietnam War but was ultimately forced to pull out and thus secured the Viet Cong’s 48

victory. As Van Hook wrote, “by failing to interdict the Ho Chi Minh trail, U.S. operations in South Vietnam were doomed to a series of pointless tactical victories… though tactical victories were many, each hill and village taken and retaken did little toward achieving the strategic goal” (Van Hook 1993, 14). Even the Tet Offensive, a series of surprise attacks by the Viet Cong in a last-ditch attempt to stop U.S. forces from gaining a final victory, was a complete operational failure for the Viet Cong, but the political and psychological effect in the United States was so devastating that it ultimately precipitated a U.S. withdrawal without victory. As another Air Force manual states, “modern wars are usually won and lost at the strategic rather than the operational or tactical level” (Sakala 1997). The Gaza Flotilla case illustrates how lawfare sometimes mitigates the risk of a tactical military success contributing to a strategic failure, but lawfare can also have the opposite result. As the following cases will illustrate, the “tactical” or “operational” success of a particular legal challenge, meaning whether it results in a legal victory, is not always aligned with its effect on the operational warfighting objective it replaces, much less the larger strategic goals for which that operation was pursued. Even when lawfare advances the same operational objective as warfare, it sometimes has different strategic consequences.

Case #1: Universal Jurisdiction Case against Doron Almog

In September 2005, lawyers at Hickman Rose, a U.K. law firm that represents the Palestinian Centre for Human Rights, got word that retired IDF Major General Doron Almog was traveling to London. On September 10, 2005, they filed a petition in a Westminster court requesting a secret arrest warrant against Almog for war crimes he allegedly committed while commanding IDF troops during the second intifada from 2001 to 2003. Chief Magistrate Timothy Workman issued the warrant for Almog’s arrest under the U.K.’s universal jurisdiction law. Anticipating the “huge significance” of the arrest, the Counterterrorism Command division of the Metropolitan Police Services (MPS) informed a number of other police agencies about the planned arrest and also consulted with an unidentified “trusted partner” that made inquiries within the Jewish community about Almog’s planned itinerary and arranged a lawyer to represent Almog (MacBrayne 2007). The next day, police also contacted Israeli national air carrier El Al to confirm Almog’s itinerary and that he had boarded his flight from Tel Aviv. Then, a team of officers waited at London Heathrow Airport for Almog’s El Al flight to land, planning to arrest him after border agents stamped his passport. However, someone – perhaps the “trusted partner”, a sympathetic officer from one of the six police agencies that were informed about the operation, or an astute El Al employee concerned about repeated police inquiries into the whereabouts of the Israeli general – tipped off the Israeli embassy in London

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that something was amiss. The Israeli Embassy then contacted Almog and advised him to remain on the aircraft when it landed. When the flight landed and Almog did not deplane, British officers approached the gate and asked for permission to board the plane. El Al refused. Two hours of tense consultations between various legal authorities at the British police headquarters ensued. The team at the airport was having trouble obtaining confirmation from police headquarters that they had the authority to forcibly board the aircraft. Moreover, the officer in charge of the operation was concerned about the possibility of an armed confrontation with Israeli air marshals that he suspected were traveling with Almog if they attempted to drag him off the aircraft (Dodd 2008). In the end, the El Al plane was allowed to leave Heathrow Airport for its scheduled return flight to Israel with Almog on board. The arrest warrant against Almog was subsequently canceled by another U.K. court (Nahmias 2005). Numerous other Israeli officials have been threatened by the possibility of arrest warrants issued under universal jurisdiction in the U.K., including Tzipi Livni, the former Israeli foreign minister for whom an arrest warrant was issued on the eve of her planned trip to London in 2009. She canceled the trip, and the warrant was subsequently withdrawn (Black and Cobain 2009a). There were also court proceedings against Israeli Defense Minister Shaul Mofaz in 2002 and 2004, as well as Israeli Defense Minister Ehud Barak in 2009 when each was traveling to Britain, but in each case, a U.K. court declined to issue a warrant (BBC 2002; McGreal 2004; Black and Cobain 2009b). Brigadier General Aviv Kokhavi also canceled plans to spend the summer at the Royal College of Defense Studies in London in 2006 due to the risk of arrest (Quetteville 2006). Beyond the U.K., there have been at least 13 similar cases involving suits against Israeli officials under universal jurisdiction in Spain, New Zealand, Belgium, Switzerland, the Netherlands, the United States, and Canada between 2001 and 2010 (NGO Monitor 2019).

Analyzing the Potency of Universal Jurisdiction Cases

If the objective of Palestinian lawfare these universal jurisdiction cases was to incapacitate Israeli political and military leaders by putting them behind bars, the tactic was a failure. None of these cases in any jurisdiction have resulted in an arrest, let alone a trial or conviction, of an Israeli official. In the case of Almog, Israel obtained knowledge about the existence of the secret warrant because someone with inside knowledge leaked the information to the Israeli embassy. Once Almog was at the airport, Britain failed to carry out the warrant due to the likely diplomatic fallout and the threat of armed conflict with Israeli air marshals. This is quite extraordinary: Israel managed to prevent British police officers from enforcing an order by a British judge on British soil with the combined threat of diplomatic pressure and

firepower. After the incident, U.K. Foreign Minister Jack Straw apologized in person to Israeli Prime Minister Ariel Sharon several days later and called the incident “very embarrassing” (Bahur-Nir 2005). Israel did not let up after the warrant was canceled, demanding changes to the U.K.’s universal jurisdiction laws. This call became more forceful after Livni canceled her 2009 visit; Israeli President Shimon Peres called the magistrate’s decision to issue a warrant a “serious mistake” and asked the U.K. to prevent such an incident from happening again (Black 2009). The universal jurisdiction statute became a central issue in U.K.-Israel relations, and in 2010 Israel also cut off routine strategic talks with Britain in protest of the universal jurisdiction law (Croft 2011). U.K. Prime Minister Gordon Brown vowed to propose changes to the U.K.’s universal jurisdiction law, and in the summer of 2010, a law was introduced that would require the Director of Public Prosecutions (a political official) to approve all future universal jurisdiction warrants (UK Parliament 2011). The Almog and Livni warrants were the central issue in the debates over the bill, and in September 2011, the changes were signed into law over the protests of human rights groups (Machover 2011). Similar changes occurred in Belgium; after the criminal complaint against Ariel Sharon was filed over alleged human rights violations by troops under his command during the Lebanese Civil War, Israel withdrew its ambassador to Belgium and demanded changes in the law. The changes were enacted the next year, and Israel reinstated normal diplomatic relations (Ratner 2003). In Spain, the universal jurisdiction law was narrowed in 2009 shortly after the Spanish high court halted an investigation of six Israeli officials into a 2002 bombing raid in Gaza under Israeli pressure (Kingston 2009). Israel has managed to alter the domestic legal landscape in the U.K., Belgium, and Spain, making it harder for these prosecutions to succeed. Israel has also opened a special counter-lawfare office within the Justice Ministry. This office has established a network of attorneys in countries with universal jurisdiction laws that are “on call” in case any legal action is taken against an Israeli citizen under the doctrine of universal jurisdiction (Kittrie 2016, 270). Israel has not only fended off universal jurisdiction cases against Israeli officers, but it has reshaped the “legal battlescape” to make it harder for these cases to be brought in the first place. However, it is likely that the Palestinian NGOs who brought these cases never intended to win a conviction. The real objective was likely to scare Israeli leaders into limiting their deployment of force on the kinetic battlefield, and in this, they were highly effective. The Almog incident led to significant public outcry in Israel, including a front-page story in the Yediot Aharonot newspaper describing “an atmosphere of hysteria in Israel’s military circles” about a possible arrest (Machover 2005). Moreover, universal jurisdiction cases, along with UN investigations and the ongoing risk of a case in the

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International Criminal Court against Israel, have prompted the IDF to institute a number of changes to Israeli battlefield tactics to minimize allegations of international law violations. Kittrie (2016) identifies the IDF’s April 2002 assault on the West Bank city of Jenin as the first time reducing civilian casualties was the primary motivating factor for a major military decision. The IDF opted for a house-by-house infantry assault instead of a bombing to reduce civilian casualties. (The operation still destroyed the center of Jenin and killed at least 22 civilians (Human Rights Watch 2000), but it was more targeted than a bombing and cost 23 IDF soldiers their lives) (Kittrie 2016). In the 2008-2009 Gaza War, Israel adopted a wider range of tactics to warn civilians before bombings, which included “distributing leaflets urging civilians to leave the conflict zone; making recorded warning calls to 160,000 Gaza phone numbers; and adopting the new “knock on the roof ” tactic of firing nonexplosive but noisy ammunition before launching an explosive attack” (Kittrie 2016, 297). Such practices were expanded in the 2014 Gaza War. Additionally, the International Law Department of the IDF (known by its Hebrew acronym DABLA) has started offering “operational legal advice” to IDF officers before and during combat operations regarding International Humanitarian Law and the Laws of Armed Conflict (Craig 2013, 9). In the 2006 Lebanon War, these lawyers were given the authority to call off an airstrike at any stage of an operation if they deem it illegal under international law (Craig 2013). Such battlefield lawyers, akin to the Judge Advocate General Corps in the United States military, are one of the most common ways of keeping combat operations in line with international law (Shapiro 2007). Israel sees these measures as weakening its tactical and operational capacity, but it adopts them anyway to minimize accusations of the IDF violating international law. Several IDF commanders have complained that the modified fighting tactics are questionable from a military perspective, as they alert militants to an imminent attack (Douek 2014). The role of combat lawyers was also criticized by a government commission appointed to investigate the IDF’s performance in the 2006 Lebanon War. The report contended that lawyers “can disrupt both the essential nature of the decisions and the military activity. It seems to us that it is appropriate that fighting forces, certainly at field ranks, concentrate on fighting and not consulting with legal advisers” (Kittrie 2016, 302). In addition to stiffening the IDF’s warfighting policies, lawfare has also enhanced the way the IDF investigates violations of those policies. Universal jurisdiction is not applicable if criminal proceedings or other “accountability proceedings” in the country where the alleged violation took place are conducted in “good faith and in accordance with international norms and standards” (Macedo 2001, 33). Thus, Israel avoids proceedings in foreign courts (and the International Criminal Court) if it can show its own investigations meet international standards. The IDF commissioned an exhaustive 900-page report after the violent 50

2010 Gaza Flotilla raid to evaluate whether IDF soldiers violated international law during the raid and whether the IDF’s mechanisms for investigating violations of the law of armed conflict met international standards (The Turkel Commission 2013). While the report concluded that Israel broadly conforms to its obligations under international law, it offered 18 recommendations for bringing IDF investigations more closely in line with international standards. One of these recommendations was to mandate that the Military Advocate General (MAG), the head of the IDF legal system, conduct a formal “fact-finding assessment” (FFA) alongside traditional operational debriefings after engagements where war crimes may have been committed so that lawyers can begin collecting evidence as soon as possible (The Turkel Commission 2013, 425-6). The IDF implemented this recommendation during the 2014 Gaza War (Kittrie 2016, 303). The most recent report about the status of these investigations, released by the MAG in August of 2018, reveals that the MAG reviewed 220 incidents on the basis of these FFAs and opened seven criminal investigations. Five of these investigations were closed without charge, and two remain ongoing. MAG has reviewed a further 360 incidents based on complaints filed by NGOs and Palestinian civilians and opened criminal investigations in 24 (Israel Defense Forces 2018). Among the investigations closed by MAG was the inquiry into the controversial Black Friday incident on August 1, 2014, which resulted in the killing of 72 Palestinian civilians in a gun battle. The only prosecution that ever resulted from these investigations was of three soldiers for theft (Cohen and Shany 2018). It remains to be seen whether these investigations will be deemed legitimate by the international community, but the high level of detail released publicly about the scope of the MAG investigation and analysis of why the investigation was closed without charge suggest that the government is seeking to justify its investigation as fair and conducted “in good faith” to prevent an investigation by the ICC or a foreign court. While it is impossible to attribute all of these changes specifically to universal jurisdiction cases against Almog and other Israeli officials, these cases undoubtedly contributed to putting pressure on Israel to institute these changes. In addition to heightening the legal limits on the IDF’s battlefield tactics, the cases were a loss for Israel at the strategic level. In 2009, Prime Minister Benjamin Netanyahu referred directly to the cases against Almog, Olmert, and Livni alongside the Iranian nuclear program and Hamas rockets in a talk about Israel’s major strategic challenges. He warned that universal jurisdiction cases, along with UN investigations into IDF activity, have “become code for a much broader phenomenon: the attempt to negate the legitimacy of our right to self-defense” (Israel Ministry of Foreign Affairs 2009.). These cases highlight alleged Israeli atrocities in the international media, leading to uncomplimentary headlines like “Israeli ex-military chief cancels trip to U.K. over threat of war crimes arrest: ‘Targeted’ actions in Gaza

Analyzing the Potency of Lawfare in the Israeli-Palestinian Conflict

may attract charges” (McGreal 2005) and “Israeli politician Tzipi Livni says British police sought to question her over war crimes” (Belfast Telegraph 2016). Even though every case has been dismissed right away, the fact that the allegations are significant enough to be reviewed by a U.K. court and generate media coverage lends a degree of legitimacy to claims that Israel is overly aggressive and acting outside of international norms. Israel’s fierce and vocal opposition to warrants also creates uncertainty over whether the decision to cancel the warrant or dismiss the case was made on the basis of political pressure, implying that the underlying case may still have merit. Whether these questions are founded or unfounded, the fact that they are raised at all carries negative strategic consequences for Israel. Israel remains one of the least popular countries in the world according to BBC World Poll, with just 25% of people viewing Israel favorably and twice that number viewing Israel unfavorably. Only Pakistan, North Korea, and Iran are viewed more unfavorably (Globescan 2017). This undeniably impedes Israel’s strategic interests in gaining allies and building international support for its policies. In sum, even when universal jurisdiction cases against are dismissed days after they are filed with no action against Israeli officials, they still have significant tactical effects on the way that Israel’s military uses force and strategic effects on Israel’s legitimacy on the world stage. Such lawfare is perhaps more potent than the traditional warfare it supplements, for it allows Palestinian NGOs to achieve military objectives without having to obtain weapons and military force in the first place.

Case #2: Targeting Hamas Finance Networks

The above case shows how Israel’s opponents have used offensive lawfare to inflict losses on Israel at all levels of war, even when Israel successfully defends against the legal cases themselves. The following case considers what can happen when Israel goes on the legal offensive. Though Israeli lawfare has taken many forms, the most frequent and successful component of this campaign has been to cut off financing for Hamas and punish banks, NGOs, and other groups that provide material support to Palestinian terror networks under the U.S. Anti-Terrorism Act. The first was the landmark case, Boim v. Holy Land Foundation, a civil suit brought in U.S. court by the family of David Boim, a 17-year-old U.S. citizen shot to death at a bus stop in the West Bank by two Hamas operatives in 1996 (Boim v. Holy Land Foundation for Relief and Dev. 2008). Nathan Lewin, the Boim family’s lawyer, developed a novel legal theory arguing that the U.S. Anti-Terrorism Act allowed plaintiffs to sue not only the actual murderers but also anyone who had contributed to the organization that carried out the attack (Kittrie 2016). The family subsequently filed a suit against the Holy Land Foundation, an American non-profit that purported to collect donations for social welfare in the Holy Land at mosques throughout the United States, then secretly funneled the proceeds to Hamas. The protracted litigation eventually

made its way to the Seventh Circuit Court of Appeals, which affirmed a lower court ruling siding with Boim’s family and awarded them $156 million in damages (Boim v. Holy Land Foundation for Relief and Dev. 2008). In his opinion, Circuit Judge Richard Posner likened giving money to Hamas to “giving a loaded gun to a child”: neither are violent, but both are “dangerous to human life” (Boim v. Holy Land Foundation for Relief and Dev. 2008, 690). The lawsuit shuttered the χ Holy Land Foundation and led to criminal prosecutions of several of its leaders. It also shut down several other terror financing networks in the United States and opened the door to subsequent litigation against organizations sending money to Hamas (Kittrie 2016). The Boim case paved the way for an even bigger lawsuit against the Arab Bank for its relationship with Hamas. The case, known as Linde v. Arab Bank, involved 297 American plaintiffs that were killed, injured, or family members of those killed by three Hamas attacks in Israel during the Second Intifada (Linde v. Arab Bank 2018). They sued the Arab Bank under the Anti-Terrorism Act for knowingly supporting Hamas’ terrorist activity by providing accounts and other banking services to Hamas and by funneling money to the group through its New York branch. In 2014, a jury found the Arab Bank liable for “providing material support for international terrorism” under the Anti-Terrorism Act, and the judge later entered a judgment ordering the Arab Bank to pay $100 million to the plaintiffs (Kim 2018). The verdict was overturned in February 2018 by a panel of judges on appeal, but the Arab Bank still paid an undisclosed settlement to the victims reportedly worth upwards of $1 billion (Kim 2018). As a result of the case, Arab Bank was forced to shut down its wire transfer service and a number of other operations in the U.S., and lawyers have subsequently filed cases against a number of European banks that allegedly transferred money to Hamas and other terrorist organizations (Kittrie 2016). At a “tactical level” of lawfare, these cases were far more successful than the Palestinian cases against Israeli officers. The victims won both major cases against groups funding or facilitating funds to Hamas, resulting in settlements worth hundreds of millions of dollars and shutting down some of the biggest Hamas funding networks in the U.S. At an operational and strategic level, these lawsuits made it harder for Hamas to raise money in the U.S. or through any organization connected to the U.S. This, combined with Israel’s blockade against Gaza, has put Hamas in a severe financial crisis. The group has reduced salaries for teachers and media personnel since 2015, and in February 2019 it shut down its al-Quds satellite TV network due to lack of funds (Amer 2019). This lawfare has clearly weakened Hamas, whose rockets are one of Israel’s main strategic threats. At the same time, this lawfare has had unintended strategic consequences that do not serve Israel’s interests. First, legal action to cut off Hamas’ funding sources has been so effective that it has completely debilitated Gaza’s economy.

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The situation in Gaza has become so severe that Israel has actually permitted donors to step in and re-inject money into the economy to prevent total collapse. Qatar has donated over $1.1 billion since 2012, including millions given directly to Hamas (Kubovich 2019). Most controversially, Israel invited Qatar to donate $90 million to pay the salaries of civil servants in Gaza over a period of six months (Schwartz, Liebermann, Dahman, and Najib 2018). When the first installment – three suitcases containing $15 million in cash – was delivered in November 2018, the Israeli government faced a storm of domestic criticism for allowing “protection money” to be paid to “criminals” (Agence France-Presse 2018). Defense Minister Avigdor Liberman eventually resigned over the deal with Hamas and pulled his party Yisrael Beiteinu from Netanyahu’s coalition, leaving the government with a razor-thin, one-seat majority in the Knesset (Harkov 2018). The funding crisis has also pushed Hamas closer to Israel’s arch-enemy Iran. Iran agreed to re-establish financial support to Hamas in March 2019, with an initial $15 annual million donation that is expected to double in the coming years (Amer 2019). Arguably, $15 million from Iranian leaders who seek Hamas’ cooperation in a regional security strategy is far more dangerous to Israel than the same amount from the anonymous American donors which the Boim and Arab Bank cases targeted. Second, despite that some of Hamas’ funds seized in the lawsuit have effectively been replenished by aid from Qatar, most Palestinians living in Gaza still face severe economic hardship. A February 2018 report by the New York Times described families from what used to be Gaza’s middle class unable to afford any food other than cooked greens meant for donkeys. “An explosion’s coming,” warned one retiree. “We have only Israel to explode against” (Halbfinger 2018). A flare-up happened just one month later with the “Great March of Return” protests organized along the Israel-Gaza border. According to Amnesty International, over 150 Palestinians were killed in the demonstrations and another 10,000 were injured (Amnesty International 2018). The protests garnered significant international press coverage, inviting criticism of the IDF’s use of force against the protesters and renewed scrutiny of Israel’s ongoing blockade of the Gaza Strip (Makdisi 2018). Another Hamas financing case had even more significant unintended consequences. In 2008, several dozen families of victims of Hamas attacks in Israel between 2006 and 2008 filed a suit in U.S. court in Los Angeles against the Bank of China for allegedly transferring money to Hamas from Syria and Iran (Areddy 2008). Several of the families were represented by Shurat HaDin, the same NGO that carried out the Gaza flotilla lawfare in 2011. According to several of the plaintiffs, the Israeli government asked them to undertake the litigation after China rebuffed Israel’s request to shut down Chinese bank accounts which Israeli intelligence services suspected of holding Hamas funds. Israeli government officials reportedly promised to provide the families with all the evidence needed to win the case in U.S. court (Kittrie 2016). The suit hinged 52

on whether the Bank of China was aware that it was facilitating terror financing at the time of the attacks. The crucial piece of evidence was testimony from former Israeli intelligence officer Uzi Shaya, who claimed that he shared evidence that the Bank of China held accounts controlled by terrorists in a meeting with bank leaders in 2005 (Kittrie 2016). After the case was filed, an Israeli intelligence official reported that the Bank of China agreed to “chang[e] its behavior” and cooperate against terrorist financing (Wultz et al. v. The State of Israel 2013, 17). Israeli leaders had achieved the “tactical objective” of the suit and asked the families if they might consider dropping the case. But the families brought the case primarily to achieve justice for their loved ones, not to take on Chinese banks. They insisted on pressing forward. As the case cleared preliminary legal hurdles and moved towards trial in 2013, China sent successive messages to Prime Minister Netanyahu threatening to cancel his upcoming state visit to China if the case went to trial and Shaya was allowed to testify (Jeremy Bob 2015). “You have committed that no current or former employee shall testify,” one letter from the Chinese read. “This commitment made it possible for you to visit China. The Chinese expect you to honor your commitment” (Wultz et al. v. The State of Israel 2013, 20). Netanyahu capitulated, wary of putting at risk Israel’s economic relationship with China and its cooperation in containing Iran (Kittrie 2016). Israel informed Shaya he was not permitted to testify, then filed a motion to quash his testimony in the case on the grounds that it would reveal sensitive national security information. The plaintiffs responded with a flurry of litigation to compel the testimony, arguing that Israel’s decision was an unjustified political decision. At that point, the case began to garner significant media attention, and several U.S. Members of Congress weighed in to advocate for the families. The Bank of China followed up with a defamation suit against the plaintiffs. After a lengthy legal battle, a judged approved the Israeli government’s request to block Shaya’s testimony, and in 2015 the entire case was dismissed (Jeremy Bob 2015). In all of these cases — even in the Bank of China case — Israel achieved the desired legal outcome. Israel’s legal campaign has succeeded in disrupting Hamas’ finance networks and severely weakened Hamas. Yet the Israeli government has struggled to contain the unintended strategic consequences of its own lawfare. Lawfare has proven to be such an effective tool against Hamas that it has helped plunge Hamas into financial crisis. The Israeli government has actually permitted financial transfers back to Hamas to prevent Gaza from collapsing completely, causing stiff domestic opposition and fractures within the Israeli government. The situation has also pushed Hamas closer to Iran and helped to aggravate the tense situation at the Gaza border. The Bank of China suit also harmed Israel’s relationship with the government of China and several of Israel’s biggest supporters in Congress, and damaged Netanyahu’s reputation as tough on terrorism (Kittrie 2016).

Analyzing the Potency of Lawfare in the Israeli-Palestinian Conflict

CONCLUSION Clearly, lawfare is a potent tool of political conflict that can achieve the same objectives as warfare under a variety of circumstances. However, the strategic implications of lawfare often differ from the warfare it supplements or replaces, and are difficult to contain. This paper considered three major cases of lawfare in the Israeli-Palestinian conflict. The first case, Shurat HaDin’s legal campaign against the 2011 Gaza flotilla, shows what happens when Israel successfully manages the tactical, operational and strategic levels of the operation. Lawfare tactics had the same operational effect as a military operation but did so without many of the strategic risks of a traditional military operation. The primary goal of the flotilla was to deliver much-needed aid to Gaza, but its strategic purpose was to focus international attention on the consequences of the blockade. The bloody 2010 raid was a failure from Israel’s perspective at this level, but lawfare campaign was inherently less dramatic and generated far less media coverage. According to Google Trends data, the 2011 flotilla generated only 15% of the number of Google searches as the 2010 flotilla that ended with the raid (Google Trends 2019). The second case involving the universal jurisdiction cases against Israeli officials appears to be a best-case scenario for Israeli defensive lawfare. The warrant against Almog was dismissed within days, no Israeli official has ever been arrested under one of these warrants, and Israel has forced changes in the laws of many European countries to make it more difficult to bring such suits. Even so, Israel struggled to manage the consequences of this lawfare. Prime Minister Netanyahu characterized these sorts of cases as among Israel’s gravest strategic threats, and Israel has adopted numerous military tactics to mitigate civilian casualties and enhanced its own investigations into allegations of war crimes. In many ways, this lawfare is more effective against Israel than an anti-aircraft or anti-missile system because it struck at the legitimacy of Israel’s political and security policies towards the Palestinians. Finally, the Hamas financing cases appeared to be a bestcase scenario for Israeli offensive lawfare. These cases all resulted in legal victory, dismantling Hamas’ funding networks and advancing the strategic objective of weakening one of Israel’s most violent enemies. But these cases had further effects that have been detrimental to Israel’s interests, creating diplomatic crises, fostering instability along Israel’s border, and opening space for increased Iranian influence. The point is that even these two best-case scenarios, where the legal outcome was highly favorable, Israel still could not contain the unintended strategic consequences of lawfare. The consequences are likely to be even more significant in a case where Israel loses the legal battle. To be sure, all weapons of political conflict (including warfare) have unintended consequences. What makes lawfare unique is that it structures these consequences in such a way that make them far more potent for Israel than for most of its adversaries. A bullet kills whomever it hits, but lawfare

is only effective against those bound by the law. Israel, with its extensive international relationships and participation in international institutions, is more ‘law-sensitive’ than Hamas or the Palestinian Authority (PA). Hamas is already considered a terrorist organization by the United States and the European Union, many countries have sanctions against Hamas, and its leaders already cannot travel to Western countries. Proceedings against Hamas in a foreign court will have little to no effect on Hamas’ operations, and it would be almost impossible to enforce any criminal penalty against Hamas. The PA has a wholly different approach to the conflict than Hamas, seeking to build its legitimacy, join international institutions, and demonstrate its capacity to govern as an independent state. However, its economic and political integration with the rest of the world is far less developed than Israel’s and under its current security arrangement with Israel it has no standing army to commit the kinds of war crimes in which Israel and Hamas are routinely accused of committing. For most of its recent history, the political rift between Hamas and the PA has divided Palestinians and served as a strategic advantage to Israel. But lawfare turns Palestinian disunity into an advantage by creating a new kind of transactional relationship between Hamas, the PA, and various non-violent Palestinian NGOs. Hamas can use its own violations of international law (by operating among civilians, for instance) to induce Israeli violations, which Palestinian NGOs can use as evidence in universal jurisdiction cases and the PA can bring to the ICC. Israel’s cooperation with Shurat HaDin can have a similar positive effect, but in the Bank of China case, that cooperation became a liability when the interests of Shurat HaDin and the Israeli government diverged. Additionally, as the Bank of China case demonstrates, the strategic outcomes of lawfare are harder to predict than the outcomes of warfare. It is clear that if you fire a missile at a Chinese ship it will provoke an aggressive response, but it is less obvious that the Chinese government will muster its full diplomatic and economic might to fight a lawsuit against the Bank of China. Because Israel has wider global links than the PA and certainly Hamas, the risk that it will miscalculate and upset a partner is higher. Lawfare is a highly potent tool of political conflict. States should not shy away from lawfare, for it is invariably preferable to using violent military force that achieves the same operational objective. However, those that wield it – especially Israel and other powerful states – must carefully contemplate the entire set of strategic implications of lawfare, for they do not always match up with the strategic implications of kinetic warfare. Moreover, lawfare makes clear that Israel’s military, economic, and diplomatic supremacy it not only insufficient to win the conflict, but it can become a liability on the front against lawfare. Israel can win many battles on many fronts against its adversaries – military, legal, and otherwise. But as lawfare demonstrates, such victories do not translate easily into a lasting victory in the larger political conflict . n

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Machover, Daniel. 2011. “Arrest Warrant Plans Make a Mockery of Universal Jurisdiction.” The Guardian. https://www.theguardian. com/commentisfree/2011/mar/30/coalition-criminal-justiceuniversal-jurisdiction (Accessed May 13, 2019). Makdisi, Saree. 2018. “The Bare Facts about the Gaza Demonstrators Are Correct, but the Rest of the Story Is Missing.” Los Angeles Times. https://www.latimes.com/opinion/op-ed/la-oe-makdisimedia-palestinian-gaza-massacre-20180406-story.html (May 13, 2019). McGreal, Chris. 2004. “Sharon’s Ally Safe from Arrest in Britain.” The Guardian. https://www.theguardian.com/world/2004/feb/11/israel. foreignpolicy (Accessed May 13, 2019). McGreal, Chris. 2005. “Israeli Ex-Military Chief Cancels Trip to UK over Threat of War Crimes Arrest.” The Guardian. https://www. theguardian.com/world/2005/sep/16/israelandthepalestinians. warcrimes (Accessed May 13, 2019). Nahmias, Roee. 2005. “U.K. Court Cancels Warrant against Almog.” Ynetnews.com. https://www.ynetnews.com/ articles/0,7340,L-3143122,00.html (Accessed May 13, 2019). NGO Monitor. 2019. Overview of Lawfare Cases Involving Israel.” https://www.ngo-monitor.org/key-issues/lawfare-internationallaw-and-human-rights/overview-of-lawfare-cases-involving-israel/ (Accessed May 13, 2019). Nicolaou-Garcia, Silvia. 2009. “European Efforts to Apply the Principle of Universal Jurisdiction Against Israeli Officials.” https:// www.middleeastmonitor.com/20090728-universal-jurisdictionagainst-israeli-officials/ (Accessed May 14, 2019). Palmer, Sir Geoffrey. 2011. Report of the Secretary-General’s Panel of Inquiry on the 31 May 2010 Flotilla Incident. United Nations. https://www.un.org/News/dh/infocus/middle_east/Gaza_Flotilla_ Panel_Report.pdf. (Accessed July 3, 2019). Quetteville, Harry de. 2006. “Israeli Army Officer Cancels UK Trip to Avoid War Charges.” The Telegraph. https://www.telegraph.co.uk/ news/worldnews/middleeast/israel/1511727/Israeli-army-officercancels-UK-trip-to-avoid-war-charges.html (Accessed May 13, 2019). Ratner, Steven R. 2003. “Belgium’s War Crimes Statute: A Postmortem.” The American Journal of International Law 97(4): 888–97. Sakala, Fredrick, “Three Levels of War.” 1997. In Air and Space Power Mentoring Guide, Maxwell AFB, AL: Air University Press. https:// www.cc.gatech.edu/~tpilsch/INTA4803TP/Articles/Three%20 Levels%20of%20War=CADRE-excerpt.pdf. (Accessed July 3, 2019). Schwartz, Michael, Oren Liebermann, Ibrahim Dahman, and Mohammed Najib. 2018. “Suitcases of $15M in Cash from Qatar Bring Relief for Gaza.” CNN. https://www.cnn.com/2018/11/11/ middleeast/gaza-qatar-humanitarian-intl/index.html (Accessed May 13, 2019). Shapiro, Ari. 2007. “JAGs Take a More Central Battlefield Role.” NPR.org. https://www.npr.org/templates/story/story. php?storyId=9371046 (Accessed May 13, 2019). The Turkel Commission. 2013. Israel’s Mechanisms for Examining and Investigating Complaints and Claims of Violations of the Laws of Armed Conflict According to International Law. The Public Commission to Examine the Maritime Incident of 31 May 2010. https://www.gov.il/BlobFolder/generalpage/alternatefiles/he/turkel_ eng_b1-474_0.pdf.

Pi Sigma Alpha Undergraduate Journal of Politics The World Bank. 2017. “Gross Domestic Product (Current US$).” https://data.worldbank.org/indicator/NY.GDP.MKTP.CD (Accessed May 12, 2019). The World Bank. 2018. “Population, total.” https://data.worldbank. org/indicator/sp.pop.totl (Accessed July 9, 2019). Toft, Monica Duffy. 2010. “Ending Civil Wars: A Case for Rebel Victory?” International Security 34(4): 7-36. Trachtman, Joel P. 2016. “Integrating Lawfare and Warfare.” Boston College International and Comparative Law Review 39(2): 267–82. United Kingdom Parliament. 2011. “Bill Stages - Police Reform and Social Responsibility Act 2011.” www. parliament.uk. https://services.parliament.uk/bills/2010-11/ policereformandsocialresponsibility/stages.html (Accessed May 13, 2019). U.S. Air Force. 2015. “Levels of War.” In Basic Doctrine - Volume 1, Maxwell Air Force Base, AL. https://www.doctrine.af.mil/ Portals/61/documents/Volume_1/Volume-1-Basic-Doctrine.pdf (Accessed July 3, 2019). Van Hook, Gordan E. 1993. Tactical Victory Leading to Strategic Defeat: Historic Examples of Hidden Failures in Operational Art. NAVAL WAR COLL NEWPORT RI. https://apps.dtic.mil/docs/ citations/ADA264169 (Accessed May 13, 2019).

Confident Women, Compassionate Leaders: The Effect of Single-Sex Education on Female Empowerment in Uganda

Confident Women, Compassionate Leaders: The Effect of Single-Sex Education on Female Empowerment in Uganda Abigail Nolan, Saint Anselm College What is the effect of single-sex education on levels of female empowerment in Uganda? It is hypothesized that a singlesex secondary school environment will produce increased levels of empowerment in female students. Empowerment is conceptualized as the amount of agency perceived in the lives of these students. To test the hypothesis, a survey was constructed, addressing the relationship between single-sex education, and indices of empowerment defined as agency. The survey was administered to a group of female students at two secondary schools in Uganda: one coeducational and one single-sex. Contrary to the hypothesis, the results of the quantitative analysis measured higher levels of empowerment in students from a coeducational environment. Analyzing the qualitative responses of the sample along the indicators of Sarah Longwe’s Women’s Empowerment Framework revealed that although students from the coed school were “more empowered,” the single-sex school seems to educate for empowerment in a different way – by teaching students to recognize barriers to their gender equality.

INTRODUCTION ingle-sex education is a controversial subject in the literature on female empowerment. Many girls who graduate from all-girls schools across the world attest to the positive impact their single-sex environment has made on them; however, others differ in their experience. Rather than serving as a tool for empowerment, some view single-sex schools as a form of gender segregation. Elizabeth Falco, a liaison for the National Coalition of Girls’ Schools, argues that “girls’ schools are successful in transforming the lives of young women because of their focused learning environment, their unique culture and climate, and the endless opportunities for leadership development” (Falco 2018). Does single-sex education have the power to transform any young girl into an empowered woman, regardless of nationality or socioeconomic status? It is hypothesized that a singlesex secondary school environment will produce increased levels of empowerment in female students. Empowerment is conceptualized as the amount of agency perceived in the lives of these students. A survey was administered, asking questions addressing the relationship between single-sex education, and various indices of empowerment defined as agency. Unexpectedly, the results of the data suggest that single-sex education does not foster higher levels of empowerment in female students when compared to a coeducational environment; however, the qualitative portions of the survey reveal a more nuanced understanding of what empowerment means to a sample of Ugandan girls. These results add to the existing literature on the issue of gender inequality and can be

used to produce policy implications that may contribute to the creation of more effective education systems in developing nations with high rates of gender inequality.

A Review of Global Gender Inequality

As a large body of existing scholarship has pointed out, gender inequality is not only a topic of academic discourse, but an issue of social and political activism (Waheed, Sayeed, Masood, and Khanam 2014). From a social and political perspective, women and men are interdependent upon each other; they work together in varying ways yet are often assigned disproportionate social and political status. This system of assigning unequal rights to men and women is often defined as gender inequality (Dorius and Firebaugh 2010; Marshall 1985; Waheed, Sayeed, Masood, and Khanam 2014). Researchers have noticed that trends in global gender inequality have experienced a steady decline over time in all nations with modern economies and political structures; however, a certain lumpiness has become apparent upon analysis of data concerning gender inequality across developing nations (Dorius and Firebaugh 2010; Dotti Sani and Quaranta 2017). Although global gender inequality across the world has been on the decline in recent years, this lumpiness refers to the existence of a large discrepancy in the data between gender inequality in Western countries, and nations in the developing world. After identifying the existence of a causal relationship between specific cultural factors in many developing nations and the degree of gender inequality prevalent in such societies, researchers have sought to identify key factors that could possibly

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be influencing this relationship. While developing nations are certainly not monolithic, a vast body of scholarship has affirmed that a country’s education system could play a major role in combating the presence of gender inequality in that country (Kane 1995; Moletsane 2005; Mensch and Lloyd 1998; Waheed, Sayeed, Masood, and Khanam 2014). This relationship between education and gender inequality stems from the rationale that education is one of the most effective methods of combatting the deeply embedded sexism prevalent in the cultural and traditional norms of societies in many developing nations. When controlling for factors such as socioeconomic status, ethnicity, location, and more, studies have found that females in developing nations are less likely to complete primary school or enroll in secondary schools than both boys in their country, and girls in more developed countries. Some of the identified barriers to education that girls 1 in developing nations commonly face include school location (i.e., difficulty commuting to school), menstruation, sexual exploitation, lack of income-earning opportunities, domestic responsibilities, and even pedagogical attitudes (Jones 2010). The issue here is that girls have been found to suffer from negative attitudes and discriminatory behaviors in the schools themselves – from both teachers and students (Jones 2010; Mensch and Lloyd 1998). Researchers argue that liberal policies alone are not enough to intervene effectively against these types of institutionalized gender inequality, calling instead for a multi-pronged approach that targets factors within the education systems themselves (Longwe 1998; Lloyd 2010; Moletsane 2005). If implemented correctly, effective education could eventually become the difference between achieving global gender equality or continuing the status quo of gender inequality in developing nations. This call for a multi-faceted approach towards education reform in developing countries is where the focus of this research diverges from existing studies on the relationship between education and gender inequality. In many developing nations, a side-effect of the institutionalized sexism prevalent in the coeducational system is a demeaning of girls’ intelligence. Previous studies have evaluated the failure of a coeducational setting to provide female students with the special encouragement needed to counteract the sexual stereotypes they encounter not only inside the school, but outside as well (Jones 2010; Mensch and Lloyd 1998; Morrell 2000). Although the debate over the effectiveness of single-sex versus coeducational models has yet to identify a true victor in any context, much can be argued in favor of single-sex education in the context of developing nations, specifically. Existing literature on the relationship between single-sex education and outcomes associated with gender inequalities has demonstrated that when implemented in specific case studies, single-sex schools have been able to improve various outcomes for their female students in developing nations (Jones 2010; Malik and Mirza 2014; Morrell 2000; Park, Behrman, and Choi 2012; Willemsen and DeJaeghere 2015). These case studies have

demonstrated a correlation between single-sex education and variables such as college attendance rates (Park, Behrman, and Choi 2012), reports of sexual harassment and awareness about sexual relationships (Jones 2010; Willemsen and DeJaeghere 2015), and factors contributing to the social climate of the classroom, particularly participation, subject choice, and utilizing education to enter the labor market (Morrell 2000). Diverging slightly from these variables, this research evaluates the extent to which single-sex education can be a determinant of female empowerment in Uganda. Understanding the link between single-sex education and female empowerment will add to the existing literature and help develop effective intervention methods for increasing female access to quality education in developing nations and global gender inequality as a whole. What is the effect of the implementation of single-sex education on levels of female empowerment in Uganda? Based on the existing literature on gender equality and education, it is hypothesized that single-sex education and female empowerment will have a positive correlation – higher levels of empowerment will be recorded in female students attending single-sex institutions than in female students attending coeducational institutions. If this hypothesis is correct, higher levels of perceived agency should be demonstrated by female students who attend single-sex schools than by female students who attend co-educational schools.

Method

As female empowerment becomes increasingly prominent as a health and development goal, a growing body of literature has sought to define and operationalize the concept. While conceptualizations of “empowerment” may vary, many scholars emphasize agency in their definition of the term (Alsop 2005; Eyben 2009; Jones 2010; Santillan et al. 2004; Schuler and Rottach 2010). In the specific context of Uganda, the Demographic and Health Surveys (DHS) Program gathered a copious amount of data on the “decision-making” process in the country. The DHS provides technical assistance to more than 300 surveys in over 90 countries, advancing global understanding of health and population trends in developing countries. This data indicates that agency is not only an accepted conceptualization of empowerment in scholarly research, but in the cultural context of Uganda as well. Generally, “agency” is defined as a person’s capacity to make effective choices and transform those choices into desired actions and outcomes. The extent to which a person is empowered is influenced by both personal agency, defined as the capacity to choose, and opportunity structure, defined as the institutional context in which the choice is made (Alsop 2005). In this study, perceived agency will serve as an indicator of empowerment. The type of educational institution – singlesex or co-ed – will be defined as the institutional context in which that agency is exercised. To better analyze the relationship between the independent variable (single-sex education) and

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the dependent variable (empowerment, defined as perception of agency), it will be important to identify alternative explanations that could also lead to empowerment in female students and control for those variables in my measurements. Some of these identified control variables include parents’ level of education, district of residence, socioeconomic status, after-school activities, presence of role models, number of siblings, academic performance, and topics of discussion in the classroom. The questions included in my survey are modeled according to this definition of empowerment (Alsop 2005; Santillan et al. 2004; Schuler and Rottach 2010) and the variables defined above. Additionally, I modeled my own questions according to the surveys designed by Jones (2010) in her study of empowerment levels of female schoolgirls in Uganda, which suggests that a single-sex environment could be a beneficial intervention method for her sample. In order to measure empowerment, a 50-question survey was administered to a total of 43 female students from two private, secondary schools in Uganda: one single-sex and one coeducational. Since I was unable to travel to Uganda to administer the survey, I worked closely throughout the survey process with Sr. Elizabeth Nakayiza, Dean of the University of Kisubi and author of Mindfulness for Educational Leadership in the 21st Century (2016). In this book, Nakayiza (2016) proposes a method for making educational systems and their curriculum leadership in Uganda relevant, functional and generative in a society where many traditional educational systems are failing. Nakayiza aided me in identifying two schools that would fit my sample criteria, obtaining informed consent from students, and administering the surveys. Nakayiza collaborated with me throughout the Institutional Review Board2 approval process, and helped me gain necessary approval from the Mildmay Uganda Research Ethics Committee (MUREC), an affiliate of the Ugandan National Council of Science and Technology. I employed a “most similar case study” design in order to compare levels of empowerment at each school; therefore, a

crucial component that I considered when choosing schools to sample from is the degree to which these two schools are similar. Factors of similarity identified include size, socioeconomic status of students, and ownership (private vs public). This similarity will be important when attempting to measure the significance of the causal relationship between single-sex education and empowerment. Two secondary schools that fit most of my criteria: St. Charles Lwanga Girls Secondary School Kalungu, an all-girls institution, and Blessed Sacrament Secondary School Kimanya, a co-educational institution. Henceforth, I will refer to these schools as “Kalungu GTC” and “Blessed Sacrament.” Table 1 lists similarities between both institutions. I used Qualtrics software to administer the online survey. The survey includes 50 multiple choice and short answer questions, addressing both my independent and dependent variables, as well as my identified control variables. Questions geared towards my independent variable (single-sex education) and dependent variable (female empowerment) measure the amount of agency perceived by students when making decisions about the trajectory of their lives, and how their education may or may not have contributed to that degree of agency. In addition, questions that address a variety of control variables measure alternative explanations for the measured effect that school type has on the amount of agency perceived by the students. While I included a variety of questions in an effort to make the survey comprehensive, the analysis focuses on questions that indicate the perceived amount of agency in the respondents’ lives. Specific questions that seek to measure agency ask respondents about what age they would like to be married in relation to the typical marriage age in Uganda, factors that influence their decision-making process, and degrees of “freedom” such as the amount of choice they have about factors that impact their futures. While the responses all provided insight into salient factors of empowerment for the students in my sample, I focus on the salience of the following open-and-close-ended questions:

Table 1: School Similarity Blessed Sacrament

Kalungu GTC

School Type

Coeducational

Single-Sex

Religious Affiliation

Roman Catholic Church

District

Masaka

Funding

Private

Teachers

More male than female

Uniforms

Yes

Curriculum

Follows national standards

Scholarships

Yes

Number of Students

1,584

363

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Q1: Empowerment is a person’s capacity to make choices freely

and realize their dreams. Based on this definition, do you think that you are empowered? Please explain.

• Yes ______________ • No ______________

Q2: Based on this definition of empowerment, do you think that your school has helped you to be more empowered? Please explain.

• Yes, my school makes me feel empowered. ______________ • N o, my school does not make me feel empowered. _____________ In the first question (Q1), I define empowerment according to my conceptualization as agency and ask specifically whether or not respondents identify with that definition of the term. The students were not given a word limit for their open-ended responses, but none exceeded twenty words. A “yes” indicates that the respondent is able to make choices freely in pursuit of their dreams, which indicates a perceived sense of agency. A “no” indicates that the respondent feels as if they do not have the capacity to make choices freely. If my hypothesis is correct, the quantitative analysis should demonstrate a higher level of empowerment in respondents from Kalungu GTC than is observed from Blessed Sacrament. The second question (Q2) builds upon Q1’s conceptualization of empowerment, testing it in a slightly different way. This question addresses the quality of education that students receive at both Kalungu GTC and Blessed Sacrament. A “yes” response indicates that respondents feel as if their school contributes to their sense of agency. A “no” response indicates that respondents feel as if their school does not contribute to their perceived sense of agency – or lack thereof. If the hypothesis is correct, more students from Kalungu GTC should say that their school makes them feel empowered.

Quantitative Analysis

Before analyzing the quantitative results of Q1 and Q2, I first test my assumption that the samples from the two schools are similar. The research design is experimental because I have assigned Kalungu GTC as my treatment group and Blessed Sacrament as my control. Although Sr. Nakayiza recommended

these schools due to the various ways in which they are similar, due to a lack of random sampling my respondents could differ along elements such as socioeconomic status, academic standing, participation in co-curriculum activities, and discussion about gender in the classroom. I chose these particular control factors because of the ways that they can impact female empowerment. If one sample of students has a higher economic status than the other, they could perceive themselves as having more opportunities and a greater sense of agency. If one sample of students identify as “more intelligent” or “of higher academic standing” than the other, those students could also see themselves as more empowered. If more students from one sample participate in co-curricular activities, such as sports, music, and dance, it could possibly affect their perceived sense of agency. Finally, I included questions about the prevalence of discussions about gender equality in my survey, in order to test the influence that those discussions may have on agency as well. The results of multiple crosstabulations and Chi Square tests on my control variables supports my assumption that the schools are similar. The results of the crosstabulations demonstrated that respondents from Blessed Sacrament were slightly different than respondents from Kalungu GTC along each of the control variables. Overall, Blessed Sacrament students were of higher economic status, in better academic standing, and participated more in co-curricular activities and discussions about gender equality (Appendix I). Although slight differences were noticed between the samples, because none of the P-values were less than .05, I cannot reject the null hypothesis that the schools do not differ on the variables in question. According to these results, there is no difference between the two schools with regard to economic status, academics, co-curriculum activities, or discussion. My assumptions that the two schools were similar are therefore supported by the data. See Appendix I for the results of the crosstabulations. Using crosstabulations, I compared the answers of respondents at each school to my crucial question (Q1) about whether or not a student perceives herself as empowered. Table 2 demonstrates a strong, negative relationship between my independent variable (single-sex education) and dependent variable (empowerment). Thus, the results indicate the opposite of my expected relationship. While 91.7% of respondents from Blessed Sacrament identify themselves as empowered, only 62.5% of respondents from Kalungu GTC

Table 2: Empowerment x School Type Crosstabulation (Q1) School Type Blessed Sacrament Empowerment No Yes

8.3% 91.7%

Note: p=.24

Kalungu GTC 37.5% 62.5%

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identify themselves as empowered. More substantially, while only 8.3% of Blessed Sacrament respondents say that they are not empowered, 37.5% of respondents from Kalungu GTC say that they are not empowered. When a Chi-Square test was performed on the data, it showed that the results of the crosstab were statistically significant at the .05 level. My second crosstabulation (Q2) corroborates the unexpected findings of Q1. Table 3 again demonstrates a strong, negative relationship between my independent variable (single-sex education) and my dependent variable (empowerment). Contrary to my hypothesis, more students from Blessed Sacrament indicated that their school made them feel empowered. While 100% of participants from Blessed Sacrament indicated that their school made them feel empowered, 93.8% of respondents from Kalungu GTC indicated the same. When a Chi-Square test was performed on the results of Q2, they were not statistically significant; therefore, I am not able to reject the null hypothesis that the difference between the responses from Kalungu GTC and Blessed Sacrament is not due to chance. This lack of statistical significance suggests that a majority of all respondents derive a sense of empowerment from their educational environment. In other words, although Blessed Sacrament respondents were more empowered than respondents from Kalungu GTC (Q1), both schools make their students feel empowered (Q2). According to the results of Q1 and Q2, it seems that a co-educational setting produces higher levels of empowerment in female students than a single-sex setting. To my surprise, the results of my quantitative analysis stand contrary to my hypothesis that higher levels of empowerment will be recorded in respondents attending single-sex schools. Although my own experience and the literature on the subject lead me to expect that respondents from the single-sex school would be more empowered than respondents from the co-ed school, there could be many explanations for this contrary result. These findings are certainly interesting, and I look to the qualitative portions of my survey results in order to gain more insight about the implications of my results.

my control variable analysis demonstrated that the samples at each school are similar, the qualitative meaning behind the responses could provide new insight into my results. More students from Kalungu GTC indicated that they were not empowered; however, both schools made a majority of their students feel empowered. It is possible that my definition of empowerment as agency is just one facet of empowerment, and there are more salient factors that students identify within this cultural context. By analyzing the qualitative responses to Q1 and Q2, I hope to gain better insight into what empowerment truly means for this sample of students in Uganda, and which factors are most salient to their perception of empowerment. Qualitative Sub-Claim: A reinterpretation of the results using qualitative analysis could suggest that coeducational schools such as Blessed Sacrament could be “schooling for subordination” rather than “educating for empowerment.” My conceptualization of empowerment as agency is rooted in the research of Dr. Shelley Jones on female empowerment in Uganda and Dr. Sarah Longwe’s Women’s Empowerment Framework. In her research, Jones (2010) did not evaluate the relationship between single-sex education and improving female outcomes; however, her analysis of the National Strategy for Girls’ Education policy in Uganda identified multiple barriers to female education and identified a call for single-sex education as a possible solution to the issue of sexual exploitation of girls while they are in school. In speaking with the students, several girls expressed their desire to attend girl-only schools because “girls are mistreated by boys, and boys end up making them pregnant” (Jones 2010, 402). In order to measure this relationship, Jones (2010) used the Women’s Empowerment Framework created by Longwe (1998), whose definition of empowerment is as follows: “Women’s empowerment is the process by which women collectively come to recognize and address the gender issues which stand in the way of their advancement. In a patriarchal society, these gender issues are the practices of gender discrimination which are entrenched in custom, law, and ideological belief.” (Longwe 1998, 19)

Qualitative Analysis

Through qualitative analysis, I hope to better explain why higher levels of empowerment are seen in female students from a coeducational setting, rather than single-sex. Although Table 3: School Empowerment x School Type Crosstabulation (Q2)

School Type Blessed Sacrament School Empowerment No Yes

0% 100%

Kalungu GTC 6.3% 93.8%

Note: p=.342

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Table 4: Women’s Empowerment Framework Welfare

measures women’s material welfare in relationship to men, incentives that enable girls to attend school

Access

concerned with equal opportunities for girls to attend school

Conscientization

extent to which students and teachers recognize gender inequalities and work towards gender-equitable relationships

Participation

refers to decision-making, leadership roles, involvement in extra-curricular activities, and having a voice in all areas of learning

Control

concerned with the balance of power between women and men

Using this definition, Longwe (1998) recognizes a difference between “education for empowerment” and “schooling for subordination”, the latter teaching women to create equitable positions for themselves within the patriarchal societies in which they live and the former encouraging women to recognize the gender inequality present in society and attempt to change the system rather than the individual (Longwe 1998). Both Jones (2010) and Longwe (1998) agree that education for empowerment is the standard by which schools should be measured. In the context of this research study, Jones’ (1998) conceptualization could serve as a basis to shed light on the true implications of my findings. Jones (2010) uses the Women’s Empowerment Framework (WEF) developed by Longwe (1998) to evaluate the extent to which the National Strategy for Girls’ Education policy has supported the empowerment of secondary schoolgirls in Uganda (Jones 2010). The WEF identifies five levels of equality and assesses empowerment by the extent to which intervention strategies address each of these levels. In

this study, the intervention strategy would be the school type: single-sex or co-ed. The five indices of this framework are defined in Table 4 (Jones 2010, 391). By analyzing the qualitative responses to both Q1 and Q2, I will use this framework to explore my contrary results further. Perhaps less Kalungu GTC respondents identified themselves as empowered because they have been educated to identify gender barriers such as lack of agency. If the hypothesis is correct, the analysis should demonstrate that more students from Kalungu GTC appeal to the five indices of the Women’s Empowerment Framework. While Q1 asked students if they are empowered based on my definition as agency, Q2 asked students if their school makes them feel empowered. By including two slightly different measures of empowerment, I hoped to produce a more informed analysis of what empowerment means to students in this cultural context. I expected to compare and contrast the responses from both questions; instead, I noticed similar trends. Many of the responses from Q2 corroborated

Figure 1: Women’s Empowerment Framework Appeals on Q1 and Q2

WEF Indicators

Control

Access

Conscientization

7 1

Participation

16 9

Welfare

Number of Times Indicator is Mentioned Kalungu GTC

Blessed Sacrament

Analyzing the Potency of Lawfare in the Israeli-Palestinian Conflict

my findings from Q1; therefore, I decided to combine the results of both to more accurately measure the responses along the WEF. Figure 1 illustrates the number of times each level of the Women’s Empowerment Framework was appealed to at each school, including the combined appeals from Q1 and Q2. See Appendices II and III for the full list of appeals on each question. My qualitative analysis hinges upon a comparison of how the respondents from each school appealed to each level of the WEF. Table 5 includes a breakdown of the coding rules for the empowerment frameworks using examples from the survey. Welfare refers to the material well-being of women in relation to men; therefore, I marked each time one of the respondents said they feel empowered because they are working to achieve a goal or realize a dream. While other studies coded welfare according to specific incentives to attend school (Jones 2010), in this study, the incentive for girls to attend school is that they view their education as a means to achievement of any kind. Respondents from both Blessed Sacrament and Kalungu GTC appealed to welfare frequently in both Q1 and Q2. For example, one Blessed Sacrament student appealed to welfare when she said that she was empowered because she has “many dreams to realize so that they can come true” (Q1). Similarly, a respondent from Kalungu GTC explained that she was empowered because, “[I] think [I] will achieve what [I] want” (Q1). The Q2 responses continued this similar appeal to welfare. Blessed Sacrament makes students feel empowered “because they set for me a ground on which I feel contented to achieve my dreams with ease” (Q2), and Kalungu GTC makes students feel empowered “because it has made me [realize] that I can be what I want to be, by giving me the best foundation” (Q2). Exactly the same frequency of appeals was

made to welfare from both schools, and respondents appealed to welfare in similar ways; therefore, they have similar levels of empowerment along this indicator. Regardless of school type, my sample of schoolgirls in Uganda identifies that setting and achieving goals is an accurate measure of empowerment in this context (Q1), and both schools contribute to a development of empowerment along this level (Q2). Participation refers primarily to decision-making, leadership roles, and extra-curricular activities. According to this conceptualization, I recorded each time a respondent explained that they believe themselves to be empowered because they are free to make their own decisions, they receive leadership development, or they attribute their empowerment to extra-curriculars. Participation was a common level of measurement for respondents at both schools, and students appealed to this level in a similar fashion. While a respondent from Blessed Sacrament said that she is empowered because she has been “given freedom to make decisions” (Q1), a respondent from Kalungu GTC attributed her sense of empowerment to “the freedom to do what I want and to decide” (Q1). One respondent from each school appealed to participation by indicating that their school makes them feel empowered because it provides opportunities to participate in co-curricular activities (Q2). One respondent from Blessed Sacrament said that her school made her feel empowered because it provided opportunities for leadership development (Q2). Although respondents from both schools appealed to participation, Blessed Sacrament demonstrated a greater frequency of appeals to participation defined as choice, which supports the findings of my qualitative analysis. This indicates that Blessed Sacrament educates for empowerment more efficiently along this indicator of empowerment.

Table 5: Coding Rules Indicator

Coding Rule

Example

Welfare

Respondent is empowered because she is working towards a goal or to realize a dream

“I think I will achieve what I want”

Access

Respondent is empowered because she is given the same opportunity as boys

“I am empowered because I was given the chance to try my luck in school which other girls do not get”

Conscientization

Respondent is empowered because she is able to recognize gender barriers – marked by any “no” response

“I am not empowered because…”

Participation

Respondent is empowered because she is free to make her own decisions

“I made a choice to stay in school and I am still there struggling for a better future”

Control

Respondent is empowered because she has autonomy in relationships with men

“Because I realized that am knowledgeable enough to say no to sugar daddies and kept schooling”

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Conscientization refers to the extent to which students recognize gender inequalities. In the context of educating for empowerment, I counted each “no” answer as a recognition of these inequalities. A “no” response indicates that the respondent perceives herself as having a lack of agency and an inability to make decisions about her own life. Kalungu GTC had a significantly greater number of “no” responses – seven from Kalungu and one from Blessed Sacrament. Of these seven “no” responses, three students said that they did not feel empowered because their parents or relatives made decisions for them: “Sometimes our relatives discourage us from what we feel we would like to be” (Q1). Interestingly enough, the only student from Blessed Sacrament who gave a “no” response also attributed her lack of empowerment to influence from family: “because I cannot make certain decisions, my parents make them for me” (Q1). While the number of responses is small, to a certain degree these results suggest that Kalungu GTC educates for empowerment, while Blessed Sacrament does not. Regardless of school type, the conscientization results are important because they demonstrate that parent influence/discouragement is a heavily cited barrier to female empowerment in this sample. A majority of Kalungu GTC respondents who said that they were not empowered attributed that lack of empowerment to influence from their parents (Q1). Additionally, all of the respondents from Kalungu who indicated that they were not empowered due to family influence or lack of agency in Q1, also indicated that their school made them feel empowered in Q2. More crucially, four respondents from Blessed Sacrament said that they feel empowered because they receive support from their parents (Q1), while none of the Kalungu GTC respondents attributed their empowerment to parental support. These results add another dimension to the initial finding about conscientization. It seems that Kalungu GTC educates for empowerment by making students aware of their lack of agency in the home; despite their awareness that they lack agency, students still indicated that their school made them feel empowered. Additionally, it is possible that more Blessed Sacrament students indicated that they feel empowered because they receive more support from their parents. This is certainly an interesting finding and warrants further research. Access is concerned with the equal opportunity of girls to attend school. A respondent from Kalungu GTC appealed to access by stating that she feels empowered because she “was given the chance to try my luck in school which other girls do not get” (Q1). Her statement insinuates that she considers herself privileged to attend school due to her gender – she has been given the opportunity to “try her luck” in a setting that other girls have not. This respondent elaborated on her appeal to access in Q2: “my school makes me feel empowered because [I] get the same opportunities others get especially the members of the opposite sex in other schools in the country.” This respondent feels that she is empowered because her single-sex environment has eliminated gender imbalances in 64

the classroom. While this certainly supports the hypothesis that a single-sex environment educates for empowerment, the response of a single student makes it difficult to generalize this finding. Control is concerned with the balance of power between men and women. One respondent from Blessed Sacrament appealed to control by touching upon her understanding of relationships with men. In stating that she is empowered because she “[realized] that [I] am [knowledgeable] enough to say no to sugar daddies and [I] kept schooling” (Q1), this respondent insinuates that she feels empowered when she seeks education instead of falling into the protection racket of a “sugar daddy.” Through her appeal to control, this Blessed Sacrament student touches upon an issue prevalent in not only Uganda, but many countries in Sub-Saharan Africa. Through these “sugar daddy” relationships with men, young women are oftentimes exploited or attempt to take advantage of such relationships to meet their basic needs, upgrade their standing and outlook among peers, and/or get money, clothes, school fees, gifts and various favors in return for sexual relationships (Kuate-Defo 2004; Luke 2005). Health organizations have deemed these men particularly problematic and have launched numerous campaigns that warn young women to “beware of sugar daddies” (Luke 2005, 6). Many studies have found that the sugar daddy phenomenon has contributed to the spread of HIV in Sub-Saharan Africa (Luke 2005). If I were given the chance to ask follow-up questions, I would have delved into this response further in order to discover how generalizable this student’s experience is in this context. The qualitative portions of Q1 and Q2 add new meaning to the results of the quantitative analysis. Although my crosstabulations (Tables 2 and 3) suggested that Blessed Sacrament students are more empowered than students from Kalungu, qualitative analysis demonstrates similarities along multiple indicators of empowerment. Respondents from both schools appealed to welfare in similar fashions and frequencies, suggesting that this sample measures empowerment equally across the sample overall, but with some key differences. Blessed Sacrament demonstrated a greater degree of empowerment as participation, supporting the results of my quantitative analysis; however, a measurement of conscientization suggests that Kalungu GTC educates for empowerment by making students aware of gender inequalities. Finally, single appeals to both access and control indicate that Kalungu GTC respondents are grateful for their singlesex environment, and Blessed Sacrament has helped female students find empowerment within their relationships with men. It is difficult to generalize these results due to the small number of responses; therefore, interviewing these respondents in greater depth could possibly reveal the extent to which their experiences are generalizable in comparison to the typical experience of girls at each of their schools. Table 6 outlines the raw number of times that various indicators of empowerment not included on the Women’s

Analyzing the Potency of Lawfare in the Israeli-Palestinian Conflict

Table 6: Outlier Indicators on Q2 School Type

Indicators Morals

Guidance

Self-Esteem

Blessed Sacrament

Kalungu GTC

Empowerment Framework were appealed to. Responses from Q1 did not stray from the five indicators on the WEF; however, a significant number of Q2 responses appealed to outside factors that add extra insight into what empowerment means for students at both schools. A significant number of respondents from Blessed Sacrament said that their school makes them feel empowered for the following reasons: it taught them right from wrong/ developed their moral compass, it increased their self-esteem, their teachers inspire and encourage them, they follow role models, and they have been given guidance/counseling. Among these trends, I would like to highlight a few interesting responses that help us to gain insight into the unique experience of female empowerment at Blessed Sacrament: “The teachers at our school always encourage me to work hard as much as the other[s] before me had done…to be successful. So they tell us to learn from the successful stories from our fellows at the university.” Blessed Sacrament makes this student feel empowered because her teachers assure her that hard work will be rewarded by success, and the school supports that claim my inviting alumni who attend university to speak with students about how they have achieved their career goals. The Blessed Sacrament alumni program supports the common findings that the presence of female role models in the lives of young women is causally linked to their level of empowerment (Bryant and Zimmerman 2003; Speizer 1981). In another survey question, many Blessed Sacrament students indicated that various female professionals were their role models because they set an example for their career goals: one, in particular, includes Honorable Rebecca Alitwala Kadaga, a Ugandan lawyer and politician who has been Speaker of the Parliament of Uganda since 2011. She inspires students “because she was able to study until…she achieved her goal of being a speaker in parliament” (Blessed Sacrament). From the Blessed Sacrament responses, it seems that simply encouraging female students to achieve their goals is extremely salient in helping them to feel empowered. Responses such as “[Blessed Sacrament] has exposed [a] hidden treasure in me that I can now stand before anyone to proclaim the truth regardless of anyone’s status and mine. All that I have I achieved from it shows that [I] am of good use to my country” (Q2) indicate this further. Outlier responses from Kalungu GTC were mostly similar to Blessed Sacrament, but with one significant difference: an appeal to the idea of womanhood. Like Blessed

Teachers

Role Models

Womanhood

Sacrament, Kalungu respondents said that their school made them feel empowered because their teachers inspire them, they are able to participate in co-curricular activities, and they are given guidance and counseling. Two respondents, however, appeal to the idea of a collective sorority or female identity by saying that their school makes them feel empowered because “it gives us a sense of order and direction hence teaching us the secrets of fascinating womanhood” and “it is because they make me feel [like I] am a lady with the duty of nurturing the world.” While neither of these students define what it means to be a “lady” or reveal the “secrets of fascinating womanhood,’ their responses indicate that one of the advantages of a singlesex setting is that students are able to cultivate a female identity. If given the chance to continue research on this finding, I would ask these respondents to define their terms and explain how a single-sex setting has contributed to the cultivation of their female identity.

CONCLUSION Crucial questions – Q1 and Q2 – ask students to indicate whether or not they are empowered according to my definition of empowerment as agency, and whether or not their school environment makes them feel empowered. The results of my initial crosstabulation between my independent and dependent variables demonstrate that respondents from Blessed Sacrament appear to be more empowered than respondents from Kalungu GTC according to my conceptualization; therefore, my hypothesis that there is a positive relationship between single-sex education and female empowerment in Uganda is unsupported by my quantitative analysis. In fact, my results demonstrated the opposite of my expectation. It seems that a coeducational environment fosters a greater sense of empowerment – defined as agency – in my sample of female students from Uganda. I tested my assumption that the samples from both schools are similar by controlling for alternative explanations such as socioeconomic status, academic standing, participation in co-curriculum activities, and discussion about gender. The results of these control crosstabulations were not statistically significant; therefore, alternative explanations cannot account for the results that stand contrary to my hypothesis. I turned to the qualitative portions of Q1 and Q2 in order to explain my quantitative findings in greater depth. Using the Women’s Empowerment Framework developed

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by Sarah Longwe, I sought to possibly redefine the results of my initial crosstabulation. According to the WEF, interventions within a school system should seek to educate for empowerment rather than a school for subordination – helping women to identify barriers to their empowerment in order to overcome them. Analyzing the responses of my sample along the indicators of this framework revealed multiple facets that in some ways supported my quantitative findings, and in other ways supported my initial hypothesis. Both schools demonstrated their ability to educate for empowerment across the WEF: both appealed to welfare in similar ways, and Blessed Sacrament appealed to control while Kalungu GTC appealed to access. The most crucial comparison between the two schools occurred along the participation and conscientization levels. Blessed Sacrament respondents demonstrated significantly higher levels of participation – empowerment as agency – which supports the results of my quantitative analysis. However, Kalungu GTC respondents demonstrated significantly higher levels of conscientization, demonstrating that they are able to recognize gender barriers. In other words, they have been educated for empowerment. Adding to this finding, I noticed a crucial difference between respondents from both schools along these indicators: support of parents. A majority of Kalungu GTC students who indicated that they are not empowered identified lack of support from parents/family as a key barrier to their agency. Additionally, the same respondents who said that they were not empowered in Q1 indicated that their school makes them feel empowered in Q2. Even more crucially, four respondents from Blessed Sacrament said that they were empowered because they receive support from their parents, while none of the Kalungu GTC respondents attributed their empowerment to parental support. While is it difficult to generalize these findings based on the responses of so few students, my qualitative analysis suggests that although Blessed Sacrament respondents were “more empowered,” Kalungu GTC seems to educate for empowerment in a different way – by teaching students to recognize barriers to their gender equality. Additionally, it suggests that lack of parental support is a major barrier to female empowerment in this sample of Ugandan students and that their school environment contributes to their sense of empowerment despite this barrier. Other factors that students from this sample identified as helpful to their empowerment are the presence of role models through alumni programs, encouragement from teachers, guidance and counseling, moral instruction, and a collective sense of what it means to be a woman in Uganda.

Limitations

In order to understand the true implications of this study, several limitations must be addressed. Firstly, with a relatively small sample (n=43), it is difficult to be certain that my findings reflect the entire population of female secondary school students in Uganda. I surveyed students from a specific 66

population – private, Catholic, secondary schools who offered both boarding and commuting options for their students. While this does not represent a majority of the population, the Ugandan Education Statistical Abstract reported that Catholicfounded institutions were the second most popular type of school in Uganda, indicating that they represent a large portion of schools and a large portion of students (Education Statistical Abstract 2016). Due to the small number of respondents, it is difficult to determine whether my sample is representative of private school students in Uganda, let alone all female students. To increase representativeness and generalizability, future research should administer surveys to four types of schools – two coeducational, and two single-sex. Stemming from the issue of a small sample size, my survey is limited to the responses of students in their perception of agency. Perceived agency is highly subjective; in order to create a fuller picture of what empowerment means in this cultural context, it would have been helpful for me to survey parents and teachers as well as students. It is possible that self-selection of parents played a role in the type of students who attended each school. The political and religious beliefs of parents could impact their choice to send their daughter to a single-sex or coeducational school. Asking the question of why parents chose Blessed Sacrament or Kalungu GTC could add insight into what empowerment means for not only the students in my sample, but their parents as well. Additionally, surveying teachers about how they measure student empowerment in the classroom could add greater depth to my research and possibly make my findings more generalizable. I measured education for empowerment according to agency, but in a classroom setting, empowerment could be measured as participation in class discussion, academic achievement, leadership roles, et cetera. One aspect of conscientization that the results of my survey did not address was the interaction between teacher and student to produce gender-equitable relationships in the classroom. Surveying teachers could also increase the objectivity of my definition of empowerment by determining how they recognize students who are empowered versus students who are not. Secondly, the nature of my experimental research design increases the likelihood that the Hawthorne effect may have shaped the results of my study and indicates that my respondents may have been biased. The students knew that they were taking part in a study interested in the relationship between female empowerment and education, which could have influenced their answers to questions such as, are you empowered? Some of my questions were leading in the sense that they provided specific definitions of empowerment and gender issues and asked to what extent each respondent resonated with those definitions. Although it was necessary for the questions to be leading in this way so that they would fit with my conceptualization of empowerment, it is very possible that respondents could have answered “yes” simply because they believed it was the “right” answer. While we cannot know for

AConfident Women, Compassionate Leaders: The Effect of Single-Sex Education on Female Empowerment in Uganda

sure, many respondents answered in the qualitative section that they were empowered because they had agency, which is simply a re-statement of the survey’s definition of the term. Thirdly, my project is limited by the inability to conduct face-to-face interviews with respondents in Uganda. Based on the results, the opportunity to interview these respondents in person would add another, deeper dimension to my project. Follow-up questions that focused on why students feel empowered or what stops them from feeling empowered would have added more validity to the qualitative analysis. It would also help determine the true meaning of empowerment in this specific, cultural context. Additionally, interviewing respondents in-person would have allowed me to delve deeper into the single responses of students who appealed to indicators of access or control.

Discussion

This project sought to make conclusive suggestions about the ways in which Uganda could implement policies that “educate to empower.” My study has corroborated the claim that education is causally linked to female empowerment, which is indicated by 97.5% (Q2) of respondents who stated that their schools made them feel empowered. Although my results cannot fully support the claim that a single-sex environment creates more empowerment in female students, the study did produce some interesting results that could possibly lead to important policy changes intended to improve education systems in Uganda. I included a number of survey questions that asked students about the presence and quality of discussions regarding gender inequality. Both the quantitative and qualitative responses to these questions indicate that students in Uganda find discussions about gender useful to them. These students also expressed a strong interest in discussing these topics more frequently in the classroom. Table 7 shows that 80.5% of respondents say that they have discussed gender at some point during their education, and 92.7% of respondents express a desire to have more conversations about topics such as the differences between gender and equality of gender. The literature addressing the value of issue-oriented discussion in a classroom setting states that the most basic purpose of discussions about topics such as gender inequality is to increase students’ awareness of their own opinions and the opinions of others in an attempt to help students reach a consensus on the issue. The literature suggests that the presence of discussions about gender could help students to better inform their

opinions (Adler et al. 2003; Gall and Gillett 1980). Taking a look at the qualitative answers to the question of why students do or do not want to have more discussions about gender in schools can illuminate the needs articulated by my female respondents in Uganda further. Regardless of school type, there were three main themes observed in the responses about why gender discussions are useful: understanding, gender equality, and self-esteem. The most popular theme in the responses appealed to gaining a better understanding about gender. Along this theme, respondents explained that discussions about gender are useful because they “help us to understand each other” (Kalungu GTC) or “enable both sexes to know about their human rights” (Blessed Sacrament). Many of the students appealed to the benefit that discussions about gender have in improving gender inequalities. Respondents explained that “in schools some boys think they are of a higher class than girls” (Blessed Sacrament) and discussions about gender “promote unity and equality [amongst] boys and girls in schools” (Blessed Sacrament). Respondents appealed to the theme of increased confidence when they said that gender discussions “help us to live in pride of what we are” (Blessed Sacrament) or “build up one’s self esteem” (Blessed Sacrament). While a majority of respondents appealed to these three trends, others also appealed to ideas such as mutual respect and providing guidelines for how to live their lives. Many studies have used the Ugandan Demographic and Health Surveys (DHS) program as a measurement of the current status of female health, economic standing, education, empowerment, et cetera. One policy implication that my results about the value of increased discussion about gender could have is the addition of questions about gender discussion into the surveys administered by the DHS. Gathering a wider range of responses to these questions could help us better understand how generalizable my findings are when broadcasted on a greater scale. Perhaps it is not the gender of the school environment that affects the level of female empowerment in Uganda, but the mere presence of both discussion and education about gender inequalities. Discussion about gender and education about empowerment can be implemented in any school setting – my research suggests that this simple policy change could benefit female students in the future.

Suggestions for Further Research

Although the limitations of my study make it difficult to generalize my findings about the relationship between singlesex education and female empowerment, some of the biggest

Table 7: Discussions About Gender Yes

Have you ever talked about the differences between boys and girls in school?

80.5%

19.5%

Would you like to talk more about topics like this in school?

92.7%

7.3%

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take-aways from my research are the lessons learned about how to better study this relationship in the future. Upon concluding this research project, I do not believe that I am able to make definitive policy recommendations about the relationship between single-sex education and female empowerment. Despite my project’s lack of generalizability, more research should most certainly be done on this topic in order to gain a better understanding of the relationship between these variables. If I were to continue my research, I would focus my research design on a mixture between surveying and in-depth interviewing rather than relying on quantitative survey alone. When reviewing the qualitative results of my survey, there were many instances where I wanted to ask multiple follow-up questions to a given response in order to gain further information about it. One quintessential example of the types of responses that prompted further investigation is from a Blessed Sacrament student who states that she sees herself as empowered because she “[realized] that [I] am [knowledgeable] enough to say no to sugar daddies and [I] kept schooling.” Many studies identify sexual health and romantic relationships as a salient indicator of empowerment (Blanc and Wolff 2001; Burns 2002; Heckert and Fabic 2013). Additionally, as I already mentioned, the “sugar daddy phenomenon” seems to be a prevalent issue in not only Uganda but all of Sub-Saharan Africa. According to my research, I have reason to believe that asking questions about romantic and sexual relationships would add more depth to this investigation; however, a simple survey likely would not be able to produce honest, accurate responses without first developing some type of trusted relationship with the respondents. Rather than empowerment in general, perhaps single-sex education could be an effective intervention strategy in attempting to combat the sugar daddy phenomenon in Uganda. Measuring this phenomenon across a greater number of single-sex and coeducational schools in Uganda using indepth interviewing, and shorter, targeted surveys would likely produce more salient findings on the relationship between single-sex education and female empowerment. n

REFERENCES Adler, Mary, Eija Rougle, Eileen Kaiser, and Samantha Caughlan. 2003. “Closing the Gap between Concept and Practice: Toward More Dialogic Discussion in the Language Arts Classroom” Journal of Adolescent and Adult Literacy 47 4): 312-322. Blanc, Ann Klimas, and Brent Wolff. 2001. “Gender and DecisionMaking over Condom Use in Two Districts in Uganda.” African Journal of Reproductive Health 5 (3): 15-28. Bryant, Alison, and Marc Zimmerman. 2003. “Role Models and Psychosocial Outcomes among African American Adolescents.” Journal of Adolescent Research 18 (1): 36-67. Burns, Kimberly. 2002. “Sexuality Education in a Girls’ School in Eastern Uganda.” Empowering Women for Gender Equity 53: 81-88. 68

Dorius, Shawn, and Glenn Firebaugh. 2010. “Trends in Global Gender Inequality.” Social Forces 88 (5): 1941-68. Dotti Sani, Giulia M., and Mario Quaranta. 2017. “The Best is Yet to Come? Attitudes toward Gender Roles among Adolescents in 36 Countries.” Sex Roles 77: 30-45. Eyben, Rosalind, and Rebecca Napier-Moore. 2009. “Choosing Words with Care? Shifting Meanings of Women’s Empowerment in International Development.” Third World Quarterly 30 (2): 285-300. Falco, Elizabeth. 2018. “Benefits of an All-Girls’ Education.” http:// www.ourkids.net/school/discover-the-benefits-of-all-girls-education (Accessed July 10, 2019). Gall, Meredith Damien, and Maxwell Gillett. 1980. “The Discussion Method in Classroom Teaching.” Theory Into Practice 19 (2): 98103. Heckert, Jessica, and Madeline Short Fabic. 2013. “Improving Data Concerning Women’s Empowerment in Sub-Saharan Africa.” Studies in Family Planning 44 (3): 319-344. Jones, Shelley Kathleen. 2010. “Girls’ Secondary Education in Uganda: Assessing Policy within the Women’s Empowerment Framework.” Gender and Education 23 (4): 385-413. Kane, Emily. 1995. “Education and Beliefs about Gender Inequality.” Social Problems 42 (1): 74-90. Kuate-Defo, Barthelemy. 2004. “Young People’s Relationships with Sugar Daddies and Sugar Mummies: What do We Know and What Do We Need to Know?” African Journal of Reproductive Health 8: 13-37. Longwe, Sarah. 1998. “Education for Women’s Empowerment or Schooling for Women’s Subordination?” Gender and Development 6 (2): 19–26. Luke, Nancy. 2005. “Confronting the ‘Sugar Daddy’ Stereotype: Age and Economic Asymmetries and Risky Sexual Behavior in Urban Kenya” International Family Planning Perspectives 31 (1): 6-14. Malik, Ra’ana, and Munwar S. Mirza. 2014. “Gender Differential Academic Achievement of Students in Single-sex and Coeducational Primary Schools in Pakistan.” Bulletin of Education and Research 1: 1-14. Marshall, Susan. 1985. “Development, Dependence, and Gender Inequality in the Third World.” International Studies Quarterly 29 (2): 217-40. Mensch, Barbara, and Cynthia Lloyd. 1998. “Gender Differences in the Schooling Experiences of Adolescents in Low-Income Countries: The Case of Kenya.” Studies in Family Planning 29(2): 167-184. Moletsane, Relebohile. 2005. “Gender Inequality in Education in the Context of the Millennium Development Goals: Challenges and Opportunities for Women.” Convergence 38 (3): 59-68. Morrell, Robert. 2000. “Considering the Case for Single-Sex Schools for Girls in South Africa.” McGill Journal of Education 35(3): 221244. Nakayiza, Elizabeth. (2016). Mindfulness for Educational Leadership in the 21st Century. XLIBRIS Corporation. Park, Hyunjoon, Jere R. Behrnman, and Jaesung Choi. 2013. “Causal Effects of Single-Sex Schools on College Entrance Exams and

AConfident Women, Compassionate Leaders: The Effect of Single-Sex Education on Female Empowerment in Uganda College Attendance: Random Assignment in Seoul High Schools.” Demography 50: 447-469. Santillan, Diana, Sidney Ruth Schuler, Hoang Tu Anh, Tran Hung Minh, Quach Thu Trang, and Nguyen Minh Duc. 2004. “Developing Indicators to Assess Women’s Empowerment in Vietnam.” Development in Practice 14 (4): 534-549. Schuler, Sidney Ruth, and Elizabeth Rottach. 2010. “Women’s Empowerment Revisited: A Case Study from Bangladesh.” Development in Practice 20(7): 840-854. Speizer, Jeanne. 1981. “Role Models, Mentors, and Sponsors: The Elusive Concepts.” The University of Chicago Press 6(4): 692-712.

NOTES 1. Gender scholars often grapple with the use of terms such as “women,” “female,” and “girls” in the literature on female empowerment. I have chosen to use the word “girl” to refer to the students in this sample because the Cambridge English Dictionary defines a “girl” as a “female child or young woman, especially one still at school.” This definition is the most accurate term to describe the population of this research. 2. A full committee review was conducted by the Saint Anselm College Institutional Review Board. Principal Investigator: Abigail Nolan. Contact irb@anselm.edu for further confirmation.

Waheed, Abdul, Afzul Sayeed, Hajra Masood, and Sameera Khanam. 2014. “Gender Inequality Among Indian Muslims: Myth and Reality.” Pakistan Journal of Women’s Studies 21(1): 29-44. Willemsen, Laura Wangsness, and Joan DeJaeghere. 2015. “Learning to Negotiate Sexual Relationships: a Girls’ School in Tanzania as a Restrictive and Agentic site.” Gender and Education 27:183-197.

APPENDICES Appendix I: Control Crosstabulations Control Crosstabulations Academic Status x School Type P=.279 Academic Status

Blessed Sacrament

Kalungu GTC

Above Average

41.70%

25.00%

Average

58.30%

75.00%

Blessed Sacrament

Kalungu GTC

Yes

75.00%

68.80%

25.00%

31.30%

Co-Curriculum Activities x School Type P=.665 Co-curric

Gender Discussion x School Type P=.872 Discussion

Blessed Sacrament

Kalungu GTC

Yes

79.20%

81.30%

20.80%

18.80%

Blessed Sacrament

Kalungu GTC

Economic Status x School Type P=.206 Economic Status

Above Average

83.30%

Not Above Average

55.90%

16.70% 44.10%

Pi Sigma Alpha Undergraduate Journal of Politics

Appendix II: Question 1— Empowerment WEF Indicators on Question 1

WEF Indicators

Control

Participation

8 5

Conscientization

Access

Welfare

Number of Times Indicator is Mentioned Kalungu GTC

Blessed Sacrament

Appendix II: Question 1 #

Blessed Sacrament

Kalungu GTC

Participation (choice)

Participation, Welfare

Self-Esteem, God

Conscientization

Control

Access

Participation (choice)

Welfare

Participation

Conscientization

Parent Support

Participation

Welfare

Support

Conscientization

Participation

Conscientization

Welfare, Participation

Conscientization

Welfare

12 13

Parent Support

Participation, Welfare

Participation

Welfare

Participation

18 19

Inconclusive

Parent Support, Participation, Welfare

Welfare

22 23

Conscientization

Support

*Note: # denotes Respondent Number

AConfident Women, Compassionate Leaders: The Effect of Single-Sex Education on Female Empowerment in Uganda

Appendix III: Question 2— School Empowerment WEF Indicators on Question 2

WEF Indicators

Welfare

Access

Conscientization

Participation

Control

Number of Times Indicator is Mentioned Kalungu GTC

Blessed Sacrament

Appendix III: Question 2 #

Blessed Sacrament

Kalungu GTC

Morals

Participation

Self-Esteem

Guidance

Participation

Access, Womanhood

Participation

Teachers, Guidance

Participation

Womanhood

Welfare

Guidance

Morals, Participation

Teachers, Role Models

Skills

Participation (co-curriculars)

Welfare

Participation, Guidance, Teachers

Participation

Welfare

12 13

Knowledge

Conscientization

Participation (co-curriculars), Teachers

Welfare

Role Models

Welfare

Teachers, Role Models

Skills

Self-Esteem

Teachers, Welfare, Participation, Morals

Teachers, Guidance

Welfare

Morals, Guidance

Guidance

Participation (leadership), Self-Esteem

Role Models

*Note: # denotes Respondent Number