Rolling the city. Tracing skaters’ network of practice in London by Ana Cristina Rodriguez Bautista

Rolling the city Tracing skaters’ network of practice in London by

Ana Cristina Rodriguez Bautista

Supervisor Dr Kerstin Sailer

September 2018

A Dissertation submitted in part fulfilment of the Degree of Master of Science Built Environment Space Syntax: Architecture and Cities Bartlett School of Architecture University College London

UCL FACULTY OF THE BUILT ENVIRONMENT BARTLETT SCHOOL OF ARCHITECTURE MSC SPACE SYNTAX: ARCHITECTURE AND CITIES

MSc Space Syntax: Architecture and Cities Dissertation Submission Form A signed and dated copy of the following MUST be inserted after the title page of the hard copy version of your dissertation. If you fail to submit this statement duly signed and dated, your submission will not be accepted for marking.

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Name: Ana Cristina Rodriguez Bautista Signed: Date:

06 September 2018

Abstract The ideas and procedures of space syntax have rarely been applied to skating, hence the combination of Borden research on the skateboarding culture (Borden, 2018), the spatial practices described by Beal’s observations (Beal, 2015) and the Koohsari studies on accessibility to open spaces with space syntax techniques served as the main theoretical guideline of this dissertation (Koohsari et al., 2013). Tracing the movement patterns of London’s’ skaters and their election of a location for their sports practice have been the motivation for the development of this research. Skating in London has a historical and worldwide famous spot underneath the Southbank Centre. Nevertheless, the existence of sixty-one skateparks in the city raised the initial research question of how the skateboarding phenomena is spatially shaped in London. The combination of space syntax techniques with social network analysis gave as main output which skateparks are chosen by the members of the skater community.

The study of the spatial practices of skaters in London from the metropolitan scale, the identification of the most popular skatepark, the preferred shared location and the final mapping of the interaction and performance of the skateparks

users correspond

the

dissertation.

This study thus offers a

main model for

finding

this

the rigorous evaluation

of the popularity of any location frequented by a specified social group. Furthermore, the main contribution of this dissertation is the proposal of a method towards the construction of the skater’s social network of practice driven by the answers of the users of the space.

Table of Contents Abstract........................................................................................................................2 List of figures………………………………………………………………………………5 - 6 List of tables……..…………………………………………………………………………................7 Acknowledgments……………………………………………………………………………8 1.Introduction ..............................................................................................................9 2.Literature Review....................................................................................................11

2.1. Brief historical sketch of skateboarding as a practice............................. 11 History of the skateboarding practice and performance interaction of users .................................................................................................................. 11 Current debate: towards an educational practice ...................................... 13 2.2. Skateboarding in London ....................................................................... 15 Southbank Core – The Undercroft, House of Vans and London Hungerford Bridge. ....................................................................................................... 15 London’s periphery skateparks: Stockwell and the Rom skateparks ......... 17 2.3. Space syntax and accessibility to open spaces and the skater community ...................................................................................................................... 19 Space syntax and accessibility to open spaces ......................................... 19 The skater community ............................................................................... 20 3.Research Methodology ..........................................................................................22

3.1. Mapping skateparks .............................................................................. 22 3.2. Data Collection (running the surveys) ................................................... 23 Seeds ........................................................................................................ 23 Snowballing sampling ................................................................................ 23 Social network analysis (SNA)................................................................... 23 Wave 1 ...................................................................................................... 24 3.3. Tracing the skateboarder’s networks of practice ................................... 25 Skateparks–skaters network (two-mode network) ..................................... 25 Skateparks–skateparks network (one-mode network) ............................... 25 Skaters–skaters network (one-mode network) .......................................... 26 3.4. Space syntax methods and skateparks’ popularity. .............................. 26 Statistical correlation.................................................................................. 26 Patterns of social interaction...................................................................... 27 4.Results of analysis .................................................................................................28

4.1.Mapping London’s skateparks infrastructure ........................................... 29 4.2. Skateparks–skaters network of practice (two-mode network) ................ 31 4.3. Skatepark–skatepark network of practice (one-mode network).............. 37 3

4.4. Skater–skater network of practice (one-mode network) ........................ 44 4.5. Closeness by distance (Correlation of NACH r: n and Euclidean distance of skaters’ houses to skateparks) .................................................................. 52 4.6. Movement pattern snapshots: Mile End skatepark................................. 76 5. Discussion .............................................................................................................85 6. Conclusions ...........................................................................................................87

List of figures

Tables

Acknowledgments My sincere gratitude to Dr. Kerstin Sailer who always kept me inspired and looking forward to testing new methods and techniques. Special thanks go to all the teachers and mentors of the Space Syntax programme for the incredible lectures we received. Likewise, many thanks to Professor Iain Borden and Rosica Pachilova for their contribution to this dissertation.

Finally, I thank my family and friends for their plenty support in all my journeys.

1. Introduction According to Borden, skateboarding has become a phenomenon and is attracting around fifty million riders across thousands of skateparks worldwide (Borden, 2018). It gathers people and creates community on streets, in skateparks or skate spots. Bruhn proposes that a community is a group that shares some common goals, values and a way of life that reinforce each other (Bruhn, 2011). This research seeks to investigate how the London’s skater’s community moves around the city and how the skateparks in the city are used.

The rapid development of skateboarding as a sport that integrates people from different backgrounds regarding age, gender or profession has increased the motivation to develop this research. In the case of London, the practice of this sport is famously recognised because of the historical skate spot underneath the Southbank Centre, known as ‘The Undercroft’. Originally, the Undercroft wasn’t conceived of as a place for skating, but since 1976 skaters have been using it (Longlivesouthbank.com, 2018). Additionally, the development of the House of Vans in 2014, an interior skatepark, just a few minutes’ walk from the Undercroft and the proposal of a skatepark underneath the Hungerford Bridge by SNE architects, might suggest that the skating culture in London centres around the Southbank area. Therefore, the research questions of this dissertation are: How is the skateboarding phenomena spatially shaped in London? Is its core, in fact, around Southbank? How is it shaped in the periphery? How do London’s skaters move around the city’s skateparks? How far do skaters live from the skateparks? Does proximity imply a frequency of use of some specific skateparks?

Building on this premise, this dissertation investigates how London’s skateparks are linked by the spatial practices of their users, examining whether there is any relationship with the topological logic of the skateparks’ distribution and the skater’s community social ties. The aim is to find the potential network of interaction among skater’s community as well as among the city’s skateparks, 9

thus verifying the usage of the city core and periphery skateparks through the use of sociometric techniques overlaid with space syntax methods.

This dissertation is structured as follows: in Chapter 2, the existing literature on the topic is summarised. Chapter 3 provides of the methodological approach and describes the analytical tools used and developed. Chapter 4 introduces the results of the quantitative and qualitative analyses. Chapter 5 discusses the main findings of the research, acknowledging how these relate to existing theories and contribute to the future expansion of spatial syntax research.

2. Literature Review The scholarly community studying skateboarding is small, nonetheless, it is currently growing. Authors such as Borden, Beal, Lombard and Carr were cited in this research in order to understand how the development of the sport practice evolved. Borden researched the history of this subculture and its relationship with space and the city (Borden, 2018); Beal explored the human interaction at the time

the

skating

performance

(Beal,

1995);

Lombard

researched

skateboarding practice as a tool for reinforcing citizenship and empowering communities by non-profit organisations (Lombard, 2015) and Carr explored the basic urban elements needed for the practice of the sport (Carr, 2010).

In the first part, the evolution of the sport – from surfing concrete waves near Venice Beach, to the establishment of a sport included in the Olympics – will be discussed. At the same time, it will be highlighted how the practice of skateboarding has been a tool for reinforcing citizenship and empowering communities by non-profit organisations. The second part explores the London skateboarding phenomena, the case of the Undercroft, London Hungerford Bridge and the House of Vans as the Southbank core. Additionally, the Rom skatepark and Stockwell will be introduced as periphery skateparks. The last part introduces space syntax and accessibly to open space literature (Koohsari et al., 2014) as well as community, co-presence and virtual community concepts (Hillier, 1996) for the overall understanding of this community’s selection of a specific place to interact.

2.1. Brief historical sketch of skateboarding as a practice History of the skateboarding practice and performance interaction of users Borden studied the history of the practice of skateboarding. It began in the mid1950s when a group of American surfers started sliding their surfboards in the promenades of Venice Beach in California (Borden, 2018). Magazines, championships

and

the

commercialisation

the

skateboards

helped 11

skateboarding break the boundaries of Venice Beach in America and become a popular practice all over the world (Borden, 2018). Even though, during the mid1980s, the practice suffered a crisis, it revived in the 1990s. Skateparks were constructed around the USA as memberships clubs were demolished, because they went bankrupt (Borden, 2018). However, when the practice revived, the investment in the construction of skateparks increased up until the point where the Olympic Committee decided to include the sport in the 2020 Summer Olympics (BBC News, 2018). Skateboarding was born as a playful experimentation of Californian surfers. Nowadays, it is a worldwide subculture and sport, which is practiced across communities and is now an Olympic sport.

Beal explained that the interaction of skaters at the time of practicing is related to the lack of a specific set of rules in skateboarding performance. Skateboarding is a democratic practice, with highly artistic performance and authentic individual and communitarian values. It promotes spatial creativity and the interaction of people of different ages (Beal, 1995).

Contrasting skateboarding with other sports, it does not use rules, referees or coaches. The lack of formal structure led to a very flexible environment where the participants not only controlled their own activity but engaged in a creative atmosphere. Skaters feel that the lack of competition enhanced opportunities for friendships and self-esteem (Beal, 1995).

On the other hand, Carr proposed that the adaptability of skateboarding to a wide variety of environment has led to the development of a variety of terrain-specific routines. Likewise, he suggested that the street and transition skating are places with a dominance in terms of popularity (Carr, 2010). Transition skating is defined by the existence of vertical surfaces such as big bowls or curved faces. “Most skaters require either a public skatepark in which the traditional features of transition skating are reproduced or substantial real estate and resources to build their own simulacrum in the form of a wooden ramp or concrete pool’’ (Carr, 2010, p. 993). 12

Current debate: towards an educational practice Currently, skateboarding phenomena is a spatial practice that some non-profit organisations teach in order to provide educational and empowerment opportunities to different social groups (Borden, 2015). Lombard, proposes spatial practice as a tool which creates community and wellbeing: “realisation of the positive role of skateboarding is being utilised for ends such as providing young people with design and technology skills, building social capital and countering societal issues from addiction to unemployment, violence, gender issues and access to education” (Lombard, 2015,pp.2).

Lombard explains how skateboarding is part of an answer to complex social conditions in the city (Lombard, 2015). The role of skateboarding as a sport, which promotes responsibility and brings health and joy to people is considered as a powerful tool that creates community and promotes wellbeing (Figure 1).

Figure 1. Learning to skate. Refugee camp, Jordan. By Daniel Zvereff.

Skateboarding, as an educational practice, has also been developed by big brands such as Vans and Nike, which have skate schools in various cities around the world. In the case of London, the House of Vans underneath the vaults of Waterloo Station was conceived as a multifunctional venue, designed for the spread of the skating culture (Figure 2). Films, exhibitions, ramps, and a bowl 13

promote skating through open classes and special events such as the monthly Girls Night (House of Vans London, 2018). On the other hand, Bay Sixty 6, sponsored by Nike, constructed a skatepark in West London which also promotes skate lessons for users of different ages (BAYSIXTY6 Skate Park, 2018).

Figure 2. House of Vans. Girls night. Author.

Skateboarding practice, therefore evolved from an informal practice in America to a sport recently added to the Olympics (Borden, 2018). Additionally, skaters’ performance has some specific socio-spatial conditions, characterised by the lack of a formal structure, which leads to a relaxed interaction among skaters (Beal, 1995). Moreover, the necessity of some specific infrastructure to the sport practice, such as vertical surfaces, was highlighted (Carr, 2010). Finally, skateboarding is proposed as a spatial practice that brings health, joy and wellbeing to its participants as a tool to teach and promote positive values among community members (Lombard, 2015).

2.2. Skateboarding in London London most famous skate spot is represented by the Undercroft in the Southbank Centre (SBC). It is recognised worldwide because of its usage over time, even though it was designed as the Festival Wing of the SBC. “Over the last few years, it has been subjected to dispute because of heritage issues, appropriation of public space and cultural value” (Lombard, 2015a, p. 91). On the other hand, the Southbank core has grown in terms of the development of new skateparks. Southbank Core – The Undercroft, House of Vans and London Hungerford Bridge. The Undercroft, one of the most famous skate spots in London, is located on the ground level of the Southbank Centre (SBC). In the beginning, it wasn’t conceived as a place for skating. However, because of its particular physical characteristics, London’s skaters have appropriated the space since 1973 (Figure 3). The ground level, with meandering walkways, concrete slopes, and curious Doric mushroom columns, is still occupied by skaters to this day (Lombard, 2015). The use of the spot since the mid 70’s represents how powerful skateboarding is in order to activate public spaces. According to Lombard, the Undercroft represents a truly public space in action that was activated by the skaters (Lombard, 2015). “Skateboarders extend the hours of the use of public spaces. Many nonskateboarders are attracted to spaces where people skateboard, just to watch the activity” (Borden, 2018, pp.216).

Currently, Long Live South Bank, a non-profit organisation that was born as a campaign to defend the Undercroft skate spot won a legal guarantee of the place for the future (Llsb.com, 2018). SBC was supposed to be restored and the skaters were going to be moved underneath Hungerford Bridge.

Figure 3. The Undercroft, 1973. South Bank Centre. http://www.llsb.com/theproject/

The design of a Hungerford Bridge project, a landscape proposal which integrates the skater and non-skater communities is an urban square developed by SNE architects, a Danish architecture studio which proposed the project in 2013 (Figure 4). The project was developed under the frame of a competition which sought to integrate skate culture with graffiti, dance and conventional recreation, moving the historical spot of the Undercroft to the surroundings of the Southbank area, due to a massive restoration project of the SBC (Snearchitects.com, 2018). It was argued that the viability of Hungerford Bridge is currently uncertain because of the decision that retaining the skate spot might have had some impact upon the SBA finances (Lombard, 2015).

Figure 4. Hungerford Bridge proposal. SNE Architects https://www.architectsjournal.co.uk/home/danish-practicewins-contest-for-new-1m-southbank-skatepark/8654173.article

London’s periphery skateparks: Stockwell and the Rom skateparks Skateboarding practice in London’s periphery has importance as well. Skateparks such Stockwell in South London (Figure 5) and the Rom in East London (Figure 6) are famous because of their bowls and ramps, also because they had organised community around them and because of their historical importance.

Stockwell skatepark opened in 1978 after initial funding from Lambeth Council, the attraction is free and open 24 hours. Friends of Stockwell Skatepark organisation takes care and makes neighbours and users aware of the park’s current situation with the new development around it. The aim of Stockwell Skatepark organisation (SSO) is to preserve the skatepark and to highlight its importance in the neighbourhood and the city. Stockwell skatepark was listed in 2015 as an Asset of Community Value by Lambeth Council, which means that the market should be put on the public market for sale, however SSO is currently negotiating for avoiding changes in the original infrastructure (Brixton Buzz news, features and listings for Brixton, London, 2018).

Figure 5. Stockwell skatepark. Author.

The Rom represents the first skatepark built in the UK; it was constructed in 1978 by Adrian Rolt and G-force, famous skatepark designers of the period. The Rom also is a unique skatepark in Europe and the second in the world added to the USA’s National Register of Historic places in October of 2013 (The Guardian, 2018). “The Rom is to be Grade II listed, English Heritage, joining the Victorian cricket pavilions and art deco swimming pools more readily associated with Britain’s built sporting heritage” (The Guardian, 2018). Figure 6 illustrates a jam performance, part of the events organised in the location.

Figure 6. The Rom skatepark. http://www.romskatepark.co.uk/about/

Skateboarding in London, therefore goes from the appropriation of public space in the city centre to initial skateparks developed in the periphery. The Undercroft, House of Vans and the Hungerford Bridge project are the core location whereas the Stockwell and the Rom represent heritage and community organisations in peripheral locations.

2.3. Space syntax and accessibility to open spaces and the skater community Despite the lack of research in the skateboarding and the space syntax before, the literature on urban spaces and physical activity (Koohsari et al., 2014) in combination with accessibility to open public spaces (Cohen et al., 2007) helped in the adoption of the theoretical framework of this study. Moreover, the explanation of the microstructure of the urban spatial environment and the patterns of co-presence among the members of a community helped in understanding the distribution of people in physical space (Hillier, 1996). Beal’s observations of the skaters community provided a general overview of their behaviour at the time of the sport’s practice (Beal, 1995).

Space syntax and accessibility to open spaces The main concern of this research is to use space syntax techniques as the primary method in order to understand how London’s skaters move around skateparks. ‘Space syntax is a set of techniques for the representation, qualification and interpretation of spatial configuration in buildings and settlements’ (Hillier et al., 1987, p. 363). Space syntax has the ability to enlarge the research dimension on public open space and physical activity (Koohsari et al., 2014). Therefore, the use of space syntax tools will contribute to our understanding of skateboarding practice in London, particularly, the relationships of the city’s skateparks with the spatial practices of its users.

Koohsari explains the role of spatial configuration on people’s behaviour, specifically the use of parks and open public spaces according to their 19

embeddedness in the street network. The relationship between proximity and physical activity was addressed in his studies by the use of space syntax methods. “Space syntax methods can provide a deeper understanding of how the design of public space can shape individual and collective behaviour” (Koohsari et al., 2014, p. 214).

The contrast between metric and topological travel distances was done by Koohsari and according to him, it would affect the selection of which park is going to be used. “The more space is integrated, the greater the chances that it will be more densely occupied by moving people” (Peponis et al., 1997, p. 344).

On the other hand, Cohen’s research proposes that the use of parks fluctuates according to features such as accessibility, availability and the quality of amenities. The development of an investigation in L.A. of how residents in low income, minority communities use public spaces and how parks contribute to physical activity was done by Cohen. Cohen’s systematic method of observation and surveys in parks to document gender and age group helped to understand the use of parks and their relationship with physical activity (Cohen et al., 2007).

The skater community A community is represented by a group of individuals related because they shared common values in certain geographical location (Bruhn, 2011, p. 12). In the case of this research, the skater community is going to be studied; individuals’ behaviour and the interaction of the community members in skateparks is the main focus of this section. Beal’s research in America helped in the development of the theoretical frame. Her observations and interviews of skaters helped to understand this community behaviour (Beal, 1995).

The space use was proposed by Hillier as the relationship of the spatial configuration and the movement patterns of people. Also, the physical distribution of people in space was defined by Hillier as virtual communities (Hillier, 1996). 20

Hillier’s concept of “co-presence, meaning the proximity of a group of people who share and use the same physical space even if they do not know each other” (Hillier, 1996, p.141), suggest that skateparks’ users are the raw material for the creation of the skater community.

The social behaviour of the skater community was observed by Becky Beal for two years in the United States (Beal, 1995). Her research highlights how skateboarding practice is quite different from that of other sports; the nonexistence of competition and inclusion of the community members were the main characteristics Beal identified. The difference between skateboarding and other sports is its freedom in terms of rules, referees or coaches (Beal, 1995). According to a skater interviewed by Beal, skating is all based on being creative with the mind, it starts in the mind and then this creativity is manifested in tricks and movement (Beal, 1995), a fact that reinforces the necessity of the study of the skateparks users’ interaction.

The combination of literature on topics of urban spaces and physical activity with accessibility to open public spaces helped to create a theoretical background for this study to understand of the movement of a specific social group in an open space. Additionally, Hillier’s definition of co-presence and the creation of community facilitated the comprehension of the interaction between skaters at the time of performing, which was reinforced with Beal’s research.

3. Research Methodology This chapter explains the research methods applied for mapping the spatial practices of the skatepark users and the further identification of a potential connection between them. Space syntax tools (Hillier & Hanson, 1984) in combination with social network analysis (Hannerman and Riddle, 2005) were the main tools used to structure this section.

The methodology was established through a pilot in four skateparks, one of them located in the city’s Southbank core and the three others in London’s Zone 2: the Undercroft, Stockwell, Clapham Common and Mile End. The pilot consisted of asking eight people in each park to fill out a survey (Appendix 1), which asked them their age, gender, which other skateparks they visited and what they would improve in terms of the skatepark infrastructure. This test was used to start tracing the spatial network of practice of London’s skaters with the initial information provided by 32 skatepark users.

3.1. Mapping skateparks The use of the data recorded by Londonskateparks, a British skateboarders organisation which maps and promotes the sport online, in combination with Google Earth observation of the skateparks’ infrastructure, was the main source used to map 61 skateparks around the Greater London area and one in the Netherlands. (Londonskateparks.co.uk, 2018).

The skateparks were categorised into six infrastructure types: two bowl categories, three ramp categories and one referring to a concrete park. The first type was divided into bowl locations, and bowl and parks locations (bowls, flatlands, benches, railings). The second locations were divided according to the ramps’ material (concrete, metal and wood). The third were spot locations, flatlands, benches and railings.

3.2. Data Collection (running the surveys) Seeds The initial seeds (starting skateparks) where the surveys (Appendix 2) were run followed the logic of two core and two periphery skateparks. The core skateparks were chosen because they were located around the Southbank area, while the two peripherals were selected because the local community sponsors them.

The skateparks selected around the Southbank core were the Undercroft and the House of Vans. Additionally, the peripherals ones were the Rom skatepark (Hornchurch) and the Stockwell skatepark (Brixton). In each skatepark, ten users were chosen for participation. The preference of a mixed population, older than sixteen years and a balance between genders were the main premises for data collection. Snowballing sampling Snowballing or chain referral sampling is a method usually used in qualitative sociological research. It consists in studying a sample through referrals made among people who share or know of others who have some characteristics that are of research interest (Biernacki and Waldorf, 1981). The combination of snowballing sampling with social network analysis techniques (SNA), guided the final plan of data collection around the skateparks.

Social network analysis (SNA) SNA acknowledges the relationships among social entities. Considering the patterns and implications of these social entities, it analyses the embeddedness of actors in their work through mathematical sociology (Wasserman and Faust, 1994). This method was used in the final data collection and the later construction of the skater community’s network of practice.

SNA introduces a framework to test theories about structures of social relationships, using sociograms as their graphic representation. People or social units are represented by points (nodes) and the relationship among pairs or people are represented by lines (ties) (Wasserman and Faust, 1994, p. 12). In this study, the nodes correspond either to the skateparks or the skaters, whereas the ties are the connections among them. SNA helped to create the networks of interaction among skateparks (one-mode networks), as well as their mutual relationship (two-mode network).

The measurement of these relationships was done through the degree of nodes which quantify the activity of the actor; this is the basis for identifying the most influential node (Wasserman and Faust, 1994, p.100). Tie strength is defined by the linear combination of mutuality (Granovetter, 1983). In the case of space syntax theory, the degree can be translated to connectivity, which measures the number of spaces immediately connecting a space of origin (Hillier and Hanson, 1984), whereas tie strength helps to measure the area network density (Han, n.d.).

After processing the information gathered in the four initial seeds, a two-mode network scheme was created using Gephi, an open source software (Bastian et al., n.d.). Four more locations were selected from the nominated skateparks, according to higher degree values.

Wave 1 Mile End, Clapham Common, Bay Sixty 6 and Crystal Palace were the skateparks visited during this phase. Ten users in each location were selected to do the survey.

3.3. Tracing the skateboarder’s network of practice Subsequently, the collection and mapping of the data gathered in the eight skateparks constructed the two-mode network among skateparks and their users. The data was processed and geo-referenced in Gephi (Bastian et al., n.d.).

Gephi allowed the researcher to split the data into two different one-mode networks. Each of these networks contained one type of node.

1. Skateparks—skateparks: this network shows where the shared practice locations are. 2. Skaters—skaters: this network shows how skaters are connected if they use the same skatepark.

This method allowed the researcher to trace and highlight the main characteristics of the three final traced networks of practice: the skateparks— skaters network, the skateparks—skateparks network and the skaters–skaters network.

Skateparks–skaters network (two-mode network) 80 interviewed users in the eight base locations represent the actors, while the 62 (one of them outside the UK) nominated skateparks represent the locations. The data was imported to Gephi for the network construction.

Skateparks–skateparks network (one-mode network) This network was obtained after splitting the two-mode network data in Gephi. The software allows changing the diameter of the nodes (skateparks) according to diverse measurements. In this case, the use of the degree showed the shared practice locations according to the node size. Additionally, Gephi makes it

possible to add specific information about each node. The type of infrastructure was added as well, and they were geo-referenced.

Skaters–skaters network (one-mode network) This network was generated after processing the two-mode network data in Gephi. The relationship among the skaters was highlighted according to the degree measurement (Wasserman and Faust, 1994). In this case, degree levels show how many skaters share the same skatepark. Gender, age ranges, profession, usage frequency, skateparks location and infrastructure were added to each node.

3.4. Space syntax methods and skateparks’ popularity. After the data collection and network mapping, space syntax techniques were overlaid. This section shows the methods used to analyse the popularity and the preferred shared location among the skater community. This was done by correlating syntactical values with user’s travel distances. Likewise, social interaction patterns were highlighted with space syntax methods: traces and snapshot.

Statistical correlation Statistical correlation was used to identify the popular and preferred shared locations of skateboarding practice. Obtained with SNA methods, this was done by taking as the starting point the data gathered in the eight visited skateparks. The locations of the users’ residences were asked and mapped. Also, the Euclidean distance from the users’ residences to the skateparks was calculated. The idea was to test if proximity implies a frequency of skatepark usage and if it has a relationship with the social ties mapped with the SNA method.

Statistical methods, specifically, correlating syntactical values of the skateparks (NACH r: n) with

the Euclidean distance from the users’ residences to 26

skateparks, was the strategy selected to highlight if the two variables were related. In space syntax theory, choice measures how likely an axial line or a street segment it is to be passed through on all shortest routes from all spaces to all other spaces in the entire system (Hillier et al., 1987). Normalised angular choice (NACH) is an average choice by total depth for each segment in the system (Hillier et al., 2012). Patterns of social interaction In order to record the behaviour of the actors in Mile End, the preferred shared location found with SNA methods, the use of space syntax observation techniques such as traces and snapshots describe the dynamic among skaters and general users in the skatepark.

First, traces of forty single individuals recorded the routes of their movements for five minutes. Inactivity and interaction among individuals are what was recorded. Second, snapshots mapped the main activities found in Mile End, differentiating between the places of interaction and non-interaction of the users as well as other activities (sitting, standing waiting to tricks, standing public). Consequently, the shape of the final methodology consisted of a combination of mapping, spatial analysis and sociometric methods that were explained in this section of the dissertation.

4. Results of analysis

London’s community of skaters and their movement around the city’s skateparks was studied in this section. The following section addresses how this phenomenon is shaped from the city scale to the human embodiment in one of the London’s skatepark. The analysis of the bonding and interaction among the members of the skater community from the traced networks was done.

Eight skateparks as interviews sites, and fifty-four additional locations served as the final data for constructing the networks. The in-depth study of the city skateparks’ networks of practice and their user’s characteristics (frequency of usage, gender, profession, and interaction during the sport practice) was done in six steps. The first one was the analysis of the skateparks’ infrastructure distribution in London. The second was the skateparks–skaters network of practice (two-mode network) showed the most popular locations among the community. The third, the skateparks–skateparks network of practice (one-mode network) showed the most shared practice locations among the interviewed users. The fourth, the skaters–skaters network of practice (one-mode network) shows the users’ characteristics. The fifth was a measurement of the popularity of the city’s skateparks by the analysis of the distance travelled to visit the skateparks, using the average NACH r: n of the destinations. Finally, after systematic observations were made in the shared practice location, movement patterns and snapshots were recorded.

4.1. Mapping London’s skateparks infrastructure The following map describes the distribution of London’s skateparks in the city. The categorisation of the skateparks was done in accordance with the main elements of a skatepark (bowls; ramps of three different materials, concrete, metal and wood; concrete parks and finally bowl and park) (Figure 7).

As a general overview, the city’s core is characterised by the presence of bowls and concrete parks, whereas the periphery has more ramps skateparks (metal, wood, and concrete). The core is represented by the ten km radius from the House of Vans area. Nineteen bowl skateparks are in London, eleven of them are in the city’s core. Additionally, eight of the nine concrete parks in London are inside the 10km core ring. These findings reinforce the fact of an inner ring of bowls and concrete skateparks.

The sum of the skateparks with ramps represents the higher amount of locations. From 61 mapped locations 29 skateparks are ramp locations (Figure 8). Nevertheless, 16 of the 29 locations are outside the ten km ratio ring. Additionally, outside the London area, four locations were mapped and three of them were ramp locations (A25, A4146, A1081). These findings suggested that the of the majority of the ramp locations are in the periphery.

4.2. Skateparks–skaters network of practice (two-mode network)

The skateparks–skaters network of practice basically traces where the skaters come from and how they are linked with the skateparks they visited. The use of degree highlights which are the locations with the most popularity. According to SNA methods, the degree represents the measure of activity of the actor it represents (Wasserman and Faust, 1994, p. 100).

Figure 8 shows the popularity of London’s skateparks: red nodes represent popular locations, green nodes the less popular locations and the grey squares represent the users’ residences. Also, the degree of each of London’s skateparks is showed in the legend of the map. From 62 mentioned locations, 61 skateparks are in London and one location is in the Netherlands. Thirty-two skateparks have a significant degree, higher than zero (legend of the map).

Moreover, an interesting fact from mapping where the skaters live is that most of the house locations generate a ring around the Undercroft. A ring of 7km from the Undercroft encloses 21 skater’s residences. Consequently, the hypothesis of an important core around the Southbank area seems to be verified with the information collected in the two-mode network of practice (Figure 8).

The initial result after tracing the two-mode network shows the historical Undercroft as the most popular location for skating. The Undercroft, with a degree of 89, represents the most nominated location among the interviewed users. Additionally, the eight interview locations demonstrated decreasing degrees of popularity, as shown in Table 1. The Rom has a degree of 53 and represents the least popular among the eight interview locations.

Table 1. Degree levels in interviews locations. Author.

From this point of the research, the prediction of the probability of which skatepark in the city is going to be the most visited was filtered by the software. Table 2 shows the locations filtered with a degree higher than 9. The most popular locations are the interview locations, with an average degree of 78.125. However, four nominated skateparks appeared in the filtered network: Victoria Park, Bloblands, Meanwhile Gardens and Folkestone Garden. These four skateparks have an average degree of 12.5. Consequently, the popularity ranges were divided in two blocks, the interview locations and the nominated locations (Table 2).

Table 2. Degree levels in eight interviews locations and four nominated locations. Author.

In the first block, the Undercroft is the most popular (degree = 89). Nonetheless the following locations don’t vary that much: Stockwell (degree = 88), Clapham Common (degree = 88) and Crystal Palace (degree = 87). The network shows these four locations as the most popular skateparks as nominated by their users. In the second block of nominated locations, Victoria Park represents the higher degree location (degree = 16) and the less popular Folkestone Garden (degree = 10) (Table 2).

According to table 2, the popularity of the skateparks in London goes around four from the eight interviews locations. The Undercroft, Stockwell, Clapham Common and Crystal Palace are the most popular skateparks in London, whereas Folkestone Garden, a nominated location, is the least popular in the filtered network.

Figure 9 shows the network of practice filtered and the locations discussed in Table 2. The map highlights the popularity around the skateparks in the city’s core and a part of the periphery (the Rom). Moreover, the network shows users’ residences and their preferred locations. The most connected user in the network is S54 (skater 54) who visits Bay Sixty 6, Undercroft, House of Vans, Stockwell, Clapham Common and Crystal Palace. From the six locations S54 visits often, four of them are the most popular locations in the network. 34

Figure 9. Skateparks - skaters network of practice. Degree range 0 - 9. Author.

The popularity of skateparks in London has a strong connection to the spatial practices of its users. The skatepark–skater network shows these relations through the measurement of skateparks’ popularity according to degree levels. Subsequently, the Undercroft, Stockwell, Clapham Common and Crystal Palace are the most popular locations in London for skateboarding practice. However, there are thirteen locations with degree = 2, which represent the least popular skateparks in the network (Table 3). Table 3. Degree levels in complete two-mode network. Author.

Since the two-mode network analysis highlights the stronger nodes – the Undercroft, Stockwell, Clapham Common and Crystal Palace –the following findings were developed in order to analyse if these locations corresponded to the most popular skateparks in the city.

4.3. Skatepark–skatepark network of practice (one-mode network) In this part of the research, the results of the skatepark–skatepark network are presented. Table 4 summarises the shared locations among the skater community to the sport practice. A shared location is defined as a skatepark with a specific number of links towards itself, it means that users of some specific locations also visit other skateparks. According to the findings, the following skateparks correspond to the preferred shared locations in London: Mile End (80 links), Clapham Common (76 links), Undercroft (64 links), Bay Sixty 6 (58 links) and Crystal Palace (58 links). Table 4. Shared locations and sum of tie strength. Author.

Figure 10 shows twenty-nine shared locations, the sum of tie strength in the nodes ratio, and 32 London’s skateparks around the traced network (Appendix 3).

What represents an important finding in this section is that the most popular skatepark found in the two-mode network does not match the favourite shared location by the skater community. The Undercroft (degree = 89) was proposed as the most popular location to the skateboarding practice, nonetheless Mile End (80 links) is the shared location most used according to the one-mode network traced.

On the one hand, eighty ties or links propose Mile-End as the most popular location in the skatepark–skatepark network of practice, whereas the second location rated in shared practice is Clapham Common, with 76 ties to other locations. Consequently, the highest sum of tie strength nominates Mile End and Clapham Common (Figure 11). The previous findings of the two-mode network highlighted the Undercroft (degree = 89), Stockwell (degree = 88), Clapham Common (degree = 88) and Crystal Palace (degree = 87). Clapham Common is the second most popular location both in the two-node network and in the nominated shared location.

On the other hand, Figure 11 shows the movement of the skater community in the periphery as well. Cantelowes, with 54 links, represents a confluence point of six London’s periphery skateparks (Hemel Hempstead, Pioneer, Harrow, Normand Park, Pollar Hill and Barking). These six locations with 22 links each, show a shared practice with less concurrence but with the potential of the creation of a periphery network with a confluence in Cantelowes, North London.

Figure 11. London's skateparks – skateparks network of practice. Cantelowes as a confluence point. Author.

The concentration of the shared practiced skateparks, in Zone 2, from Mile End (East London) to Clapham Common (South London), suggest their role as a transition to the city’s core skateparks (Figure 12). Additionally, the role of the Rom with 28 links as the periphery skatepark in the filtered network appeared as well.

Figure 12. London's skateparks–skateparks network of practice. Skateparks sum of ties > 27. Author.

The importance of the links among Mile-End, Clapham Common and the third most shared location in the network, the Undercroft (64 links) shows the existence of an important location in the city’s core. The Undercroft was nominated as the most popular location in the two-mode network, nevertheless, the Undercroft was found to be the third shared location in the skatepark–skatepark network (Figure 13). This finding suggests that the usage of a skatepark according to its high degree, or the frequency of nominations (two-mode network) against a shared location (one-mode network), can be represented by the sum of ties of a specific location. Mile End as the preferred shared location behaves as a transition to the city’s historical spot for skateboarding practice, the Undercroft (Figure 13).

Figure 13. London’s skateparks–skateparks network of practice. Skateparks sum of ties > 56. Author.

Moreover, the infrastructure characteristics of the filtered network show a concentration of bowls and concrete parks in the core of the city. Mile End, the preferred shared location has a bowl and park infrastructure, Clapham Common a concrete park, the Undercroft a concrete park, Bay Sixty 6 a bowl and park and Crystal Palace a bowl (Figure 14). These findings show that there is a higher movement of users around a network of bowls and concrete skateparks.

Figure 14. London’s skateparks–skateparks network of practice. Skateparks sum of ties > 56 with infrastructure. Author.

4.4. Skater–skater network of practice (one-mode network) The following maps (Figures 15,16,17,18) illustrates the specific characteristics of the skatepark users. The maps show information about the users’ distribution in the skateparks, the skateparks’ infrastructure (Figure 15), gender (Figure 16), age ranges (Figure 17) and users’ profession (Figure 18). The nodes were labelled by two initials S (skaters) and A (artists), with a following number, from the eighty users interviewed, seventy-eight were skaters and two were artists. All the nodes were filtered by degree; the ratio of the nodes represent the degree level (Table 5).

Figure 15 shows skateparks’ infrastructure: five from the eight locations were bowls, two of them private bowls and the three remaining were concrete skateparks.

Figure 15. London's skaters–skaters network of practice. Skateparks and infrastructure. Author.

Table 5 shows the sum of ties of each node > 99; these nodes represent the skaters who are more connected to the sample community, skaters that share the most locations. From the eight interview locations, no one from Mile End, the most frequented shared location, had more than 99 ties.

S76, a male skater interviewed in Crystal Palace, has the highest number of ties, 149, however among the eleven users highlighted, one was a female skater interviewed in Stockwell with 103 links. Table 5. Sum of ties >99, gender and shared locations. Author.

The gender difference was the most striking fact that was found. Despite the aim of the study to represent gender equally, most of the skatepark users were men (Figure 16). Of the 80 users interviewed, 82.5% were men, whereas 17.5% were females. Additionally, Mile End, the preferred shared location according to the findings of this section, did not have women as users at the time of the interviews (Figure 16). Mapping skateparks users’ gender illustrated the concentration of a 45

mixed gender usage of London’s skateparks in the city’s core (Undercroft, House of Vans, Stockwell and Clapham Common) and the connection with two external locations (Bay Sixty 6 and Crystal Palace). The Rom and Mile-End have mainly male skater populations (Figure 16).

Figure 16. London's skaters–skaters network of practice. Skater’s gender. Author.

The following sociogram illustrates skaters’ age ranges (Figure 17). The Rom users have the main characteristic of being the elder people among the network as well as a peripheric location. The Rom represents the only location of the network with an average population older than forty years old.

Figure 17. London's skaters–skaters network of practice. Skaters’ age ranges. Author.

Likewise, Mile End, the preferred shared location, has users between 16 and 25 years old, who represent the higher percentage of the age ranges. 33.75 % of the users were 16–20 years old and 27.5% were 21–25 years old. Therefore, Mile End represents a reflection of the age range of the network.

The Rom users have the specific characteristic of being less embedded in the overall network: S7 and S3 play the role of cut-points in the network (Figure 17). SNA defines a cut-point as a group of nodes which are necessary for maintaining the connectedness of a graph (Wasserman and Faust, 1994, p. 113). The Rom behaves as an excluded location of skater–skater network of practice; nonetheless it is the only location which is popular among males older than forty years old. The Undercroft, House of Vans, Clapham Common and Stockwell tend to have stronger ties among them, however the Rom skatepark could be disconnected from the network and could keep the loyalty of its users (Figure 16). 47

The skateparks user’s characteristics mapped through the one-node network tend to highlight the Rom users as the people most vulnerable of being detached from the network of practice. Additionally, Mile End, the most popular location according to the skatepark–skatepark network, represents the location with the most diversity in users’ professions: high school students, university students, professional and workers all use the location (Figure 18). On the other hand, 18 of the 40 users of the core locations are workers, who represent the highest percentage in the network (38%) (Figure 18).

Figure 18. London's skaters–skaters network of practice. Skaters’ professions. Author.

It could be the case that high number of ties and the gender distribution in the skaters’ network is related to the historical skateboarding core. The following sociogram (Figure 19) shows the city’s core and how it is linked to the periphery. The case of the nodes sum ties > 99 coincide with the nodes linked with ties weight > 2. Nodes such as S37, S38 (House of Vans) and S54 (Bay Sixty 6), correspond to the users who shared the most locations.

Table 6. Skaters – skaters network. Tie weight >2. Author.

Figure 19. Skaters – skaters network of practice. Merged findings. Author.

After analysing the users’ characteristics and how they are linked in the network of practice, it can be acknowledged that a skateboarding core in London does exist. Additionally, the average NACH r: n of each core’s locations are values from 0.9312 to 1.1974, which correspond to a medium level of NACH r: n, however, core locations have higher NACH r: n than peripheral locations, whose values are from 0.8867 to 1.0907. Finding that suggest a relationship between the core strong ties and higher NACH values. Table 7. Core Locations and NACH r:n. Author.

Table 8. Peripheral locations and NACH r: n. Author.

According to this section’s findings, London’s skateparks users’ network reinforces the existence of an inclusive core, with a variety users ages, professions and genders. A core with stronger social ties, with seven out of 40 users having total ties higher than 99 and with four locations with a higher NACH than the peripheral skateparks, are facts that prove the core’s existence. Likewise, a periphery exists, represented by four locations. Mile End was nominated as the preferred shared practice location, with a mixture of user’s professions and age ranges and the Rom’s users are loyal even though the location were to be detached from the network. 51

4.5. Closeness by distance (Correlation of NACH r: n and Euclidean distance of skaters’ houses to skateparks)

Users’ selection of locations of skateboarding practice can be associated with the topology of the street network. This section discusses the relationship of users’ travel distances to skateparks with the embeddedness of the skateparks in the street network. Additionally, the SNA findings are going to be associated with the results as well.

The data collected in the surveys were used to map where the skaters come from. The use of NACH r: n of each skatepark was taken as the main syntactical value to correlate with the travel distances of each user from their residences to the preferred skateboarding location.

The following images illustrates the average NACH r: n of each location (Figure 20, 21,22, 23, 24, 25, 26, 27). The values of choice are decreasing in the following order: Clapham Common (1.1974), the Rom (1.0907), Stockwell (1.0706), Bay Sixty 6 (0.9987), Undercroft (0.9618), House of Vans (0.9312), Mile End (0.8867), Crystal Palace (0.5165).

Figure 20. Clapham Common. NACH r: n and location images. Author.

Figure 21. The Rom. NACH r: n and location images. Author.

Figure 22. Stockwell. NACH r: n and location images. Author.

Figure 23. Bay Sixty 6. NACH r: n and location images. Author.

Figure 24. The Undercroft. NACH r: n and location images. Author.

Figure 25. House of Vans. NACH r: n and location images. Author.

Figure 26. Mile End. NACH r: n and location images. Author.

Figure 27. Crystal Palace. NACH r: n and location images. Author.

Table 9 and 10 show the distances of the skater’s residences from the seed and wave 1 locations, respectively. Table 8 highlights the average of the longest travel distances and NACH r: n values. A relationship between longer travel distances and NACH values from 0.9618 to 1.0907. The case of the Undercroft, with an average of NACH r: n 0.9618 attracts people from 20.2040 km away, whereas the Rom attracts people from an average distance of 15.0013 km. Table 9. Travel distances from skaters' residences to seed skateparks and average NACH r: n of seed skateparks. Author.

Interviews sites

ROM

HOUSE OF VANS

UNDERCROFT

STOCKWELL

TRAVEL DISTANCES FROM SKATERS' RESIDENCES TO SEEDS SKATEPARKS & AVERAGE NACH OF WAVE 1 SKATEPARKS Travel distance from skaters' Average travel distance from skaters' Users Average NACH r : n (Interviews sites) residences (km) residences to interviews sites (km) S1 12.11 S2 27.27 S3 1.67 S4 10.6 15.0013 1.0907 S5 11.88 S6 7.6 S7 18.37 S8 30.51 S11 5.96 S12 3.47 S13 6.69 S14 7.31 S15 10.5 12.4860 0.9313 S16 9.2 S17 14.12 S18 23.59 S19 17.7 S20 26.32 S21 2.12 S22 3.8 S23 4.27 S24 7.79 S25 8.32 20.2040 0.9618 S26 19.67 S27 21.87 S28 27.82 S29 45.55 S30 60.83 S31 1.2 S32 1.46 S33 3.47 S34 9.19 S35 3.9 5.4390 1.0706 S36 5.96 S37 S38 S39 S40

7.71 8.42 12.58 0.5

The Undercroft and the Rom attract users from outside London’s boundaries while The House of Vans and Stockwell attract users from the city. Stockwell brings together users that live near the skatepark (Figure 28). According to Table 9, Stockwell’s users travel on average 5.4390 km to visit the location.

Figure 28. Measurement of skateparks’ popularity. Distance from skaters’ houses to seed skateparks. Author.

Table 10 shows the average travel distances and NACH r: n values from Wave 1 skateparks. It was found that the longest travel distance corresponds to the highest NACH value. Clapham Common users travel on average a distance of 8.9060 km to reach the skatepark (NACH r: 1.1964). The shortest average distance, 3.6275 km, was travelled by Bay Sixty 6 users and it was associated with lower NACH values (0.9988). Table 10. Travel distances from skaters' residences to Wave 1 skateparks and average NACH r: n of Wave 1 skateparks. Author.

Interviews sites

MILE END

BAY SIXTY 6

CLAPHAM COMMON

CRYSTAL PALACE

TRAVEL DISTANCES FROM SKATERS' RESIDENCES TO WAVE 1 SKATEPARKS & AVERAGE NACH OF WAVE 1 SKATEPARKS Travel distance from skaters' Average travel distance from skaters' Users Average NACH r : n (Interviews sites) residences (km) residences to interviews sites (km) S39 0.26 S40 0.17 S41 0.34 S42 1.63 S43 3.75 4.7511 0.8867 S44 8.98 S45 6.39 S46 8.37 S47 12.87 S48 S49 0.4 S50 0.65 S51 1.27 S52 0.78 S53 4.85 3.6275 0.9988 S54 9.33 S55 2.48 S56 9.26 S57 S58 S59 2.25 S60 1.9 S61 3.69 S62 2.96 S63 12.18 8.9060 1.1974 S64 16.23 S65 4.21 S66 4.11 S67 6.72 S68 34.81 S69 1.16 S70 1.28 S71 3.29 S72 3.32 S73 1.41 3.9640 0.5165 S74 4.08 S75 8.7 S76 6.8 S77 4.73 S78 4.87

Figure 29 shows a map of the travel distances in Table 10. Overall, all the Wave 1 skateparks attract people from London; Clapham Common is the location which attracts one user from outside the city.

Figure 29. Measurement of skateparks’ popularity. Distance from skaters’ residences to Wave 1 skateparks. Author.

The following map shows distances from the seed and Wave 1 locations merged. The seed locations bring people from greater London and from the periphery as well, whereas the Wave 1 locations bring users from areas around the skateparks (Figure 30).

Figure 30. Measurement of skateparks popularity. Distance from skaters’ residences to Seed and Wave 1 skateparks. Author.

The Undercroft (Figure 30), represents a confluence node of the skater community; people from the periphery and from other cities come to visit this spot. However, the Rom represents an important location as well: the skatepark brings people from the periphery and brings together a specific social group. The Rom users described in the skaters–skaters network of practice correspond to a very exclusive social group (men older than forty years old) who travel no matter what the distance to the skateboarding practice.

In order to test if there is a significant relationship between the average travel distance to the skateparks and the average NACH of the each visited skatepark, the values in Tables 9 and 10 were correlated. It was expected that more accessible locations (with higher NACH r: n values) would have longer travel distances. Figure 31 shows the correlation of the table’s average values. The significance value (2-tailed) is greater than 0.05 (P = 0.464), consequently, there is no statistically significant correlation. However, R2 = 0.304 is a positive value, which corresponds to a directly proportional relationship between the correlated variables of the locations near the regression line.

Figure 31. Correlation between average travel distances from skaters’ residences to interview locations and average NACH r:n of the interview locations. Author.

Bay Sixty 6, Mile End, House of Vans, Rom and the Undercroft were the locations with the longest travel distances and the highest NACH r: n values. Finding that proposes longer travel distances with more accessible locations (Table 11). Table 11. Relationship between travel distances and average NACH. Skateparks near regression line highlighted. Author.

Interviews locations

ROM HOUSE OF VANS UNDERCROFT STOCKWELL MILE-END BAY SIXTY 6 CLAPHAM COMMON CRYSTAL PALACE

Average travel distance from skaters' residences to interviews locations (km)

Average NACH r : n (Interviews locations)

15.0013 12.4860 20.2040

1.0907 0.9313 0.9618

5.4390

1.0706

4.7511 3.6275 8.9060

0.8867 0.9988 1.1974

3.9640

0.5165

Despite the fact that the correlation was not significant, the finding of a directly proportional relationship of longer travelled distances with accessible locations (NACH r: n) proposes a second correlation.

Table 12 shows the distances from skater’s residences to the nominated skateparks from seeds locations users. Undercroft users travel the longest distances to their preferred locations (63.27 km to Folkestone Gardens NACH 0.6970), whereas most Stockwell users go to nearby skateparks or are loyal to Stockwell. Figure 32 illustrates the traces of the seed locations users shown in Table 12. The Undercroft users come from outside the city and four of the Rom users nominated the Rom as the only skatepark they visit, a finding that reinforces the strong loyalty of this social group (found in the skater–skater network section).

Table 12. Distances from skater’s residences to nominated skateparks in the seed locations. Author.

Interviews sites

Rom

Stockwell

Undercroft

House of Vans

Nominated skateparks

Travel distance from skaters' residences (km) to nominated skateparks

Average NACH r: n of nominated skateparks

Barking Rom Rom Rom Rom Rom Borough Green Mile - End Undercroft Stockwell Stockwell Crystal Palace Dartford Stockwell Crystal Palace Undercroft Stockwell Crystal Palace Clapham Common Dartford Stockwell Undercroft Bloblands Telegraph Hill Mile End Folkestone Gardens Stockwell Crystal Palace Royal Oak Crystal Palace Clissold Park Harrow Victoria Park Undercroft Bay Sixty 6 Mile - End Undercroft Undercroft Folkestone Garden Claphman Common Undercroft Undercroft Cantelowes Undercroft Hemel Hempstead Harrow Mile - End Mile -End Victorial Park Harrow Mile End Bay Sixty 6 Undercroft Undercroft Mile - end Cantelowes Undercroft Undercroft Mile - End Stockwell Clapham Common Undercroft Stockwell Clapham Common Undercroft Bay Sixty 6

33.72 1.66 18.28 12.16 7.62 11.88 0.47 5.37 11.26 3.49 7.72 6 15.59 0.51 6.34 4.08 1.22 6.2 7.7 27.15 3.89 17.01 3.33 1.29 6.32 2.48 5.95 3.03 8.44 9.03 21.73 24.05 24.77 45.55 6.34 13.91 4.26 60.83 63.27 3.51 21.89 19.64 1.46 5.96 12.76 8.73 22.07 3.48 2.56 1.53 22.18 11.27 17.4 9.94 8.07 14.79 5.38 23.85 18.82 1.03 3 4.16 3.59 4.04 8.1 11.91

0.844419 1.09072502 1.09072502 1.09072502 1.09072502 1.09072502 1.09072502 0.886735733 0.96181113 1.070646727 1.070646727 0.516547665 out of London 1.070646727 0.516547665 0.96181113 1.070646727 0.516547665 1.19743232 out of London 1.070646727 0.96181113 0.66449836 0.90763183 0.886735733 0.69706303 1.070646727 0.516547665 1.2263159 0.516547665 0.893918185 out of London 0.957734315 0.96181113 0.99878895 0.886735733 0.96181113 0.96181113 0.69706303 1.19743232 0.96181113 0.96181113 1.3862913 0.96181113 out of London out of London 0.886735733 0.886735733 0.957734315 out of London 0.886735733 0.99878895 0.96181113 0.96181113 0.886735733 1.3862913 0.96181113 0.96181113 0.886735733 1.070646727 1.19743232 0.96181113 1.070646727 1.19743232 0.96181113 0.99878895

Figure 32. Measurement of skateparks’ popularity. Distance from skaters’ houses to nominated skateparks in seeds. Author.

Table 13 shows travel distances of Wave 1 users from their residences to the skateparks they nominated; as a general insight, travel distances tend to be < 15km. Clapham Common users travel the longest distances to their preferred skateparks, 41.44 km to visit Pollar Hill (NACH 0.8362) and 26.88km to Meanwhile Gardens (NACH 0.8916). Table 13. Distances from skater’s residences to nominated skateparks in the wave 1 locations. Author.

Interviews sites

Mile - End

Bay Sixty 6

Clapham Common

Crystal Palace

Nominated skateparks

Travel distance from skaters' residences (km) to nominated skateparks

Average NACH r: n of nominated skateparks

Mile - End Mile -End Barking Victoria Park Undercroft Mile - End Clapham Common Bay Sixty 6 Victoria Park Stockwell Mile - End Victoria Park Finsbury Mile - End Bay Sixty 6 Bay Sixty 6 Meanwhile Gardens Cantelowes Victoria Park Clapham Common Stockwell House of Vans Undercroft Meanwhile Gardens Bay Sixty 6 Royal Oak River Brent Meanwhile Gardens Bay Sixty 6 Royal Oak Meanwhile Gardens Mile - end Meanwhile Gardens Royal Oak Crystal Palace Clapham Common Stockwell Bloblands House of Vans Clapham Common Stockwell Undercroft Lloyds Park Mile - End Stockwell Clapham Common Stockwell Clapham Common Undercroft Mile - end Pioneer Hemel Hempstead Meanwhile Gardens Cantelowes Pollar Hill Victoria Park Clapham Common Crystal Palace Crystal Palace Clapham Common Folkestone Garden Peckham Rye Crystal Palace Bloblands Charlton Mudchute Mile - End Clapham Common Stockwell Mudchute Pollar Hill Bloblands Stockwell Crystal Palace Mile - End Stockwell Crystal Palace

0.33 0.27 0.33 8.08 14.25 12.86 11.6 13.26 1.82 13.23 6.39 1.48 1.46 8.98 1.27 0.43 0.54 1.61 7.22 3.93 1.98 3.23 3.87 2.78 2.47 1.05 5.94 9.42 9.27 10.29 0.87 12.67 1.02 1.83 2.82 4.21 3.98 1.08 7.83 4.12 5.92 9.49 1.15 7.46 1.01 1.9 3.89 2.16 5.68 11.08 1.68 9.67 26.88 26.8 41.33 4.47 11.43 11.56 10.05 2.95 7.13 3 3.32 3.08 1.95 4.84 7.5 4.25 4.76 10.4 2.32 3.21 2.43 1.29 11.4 7.2 6.8

0.886735733 0.886735733 0.844419 0.957734315 0.96181113 0.886735733 1.19743232 0.99878895 0.957734315 1.070646727 0.886735733 0.957734315 1.0673258 0.886735733 0.99878895 0.99878895 0.89164575 1.3862913 0.957734315 1.19743232 1.070646727 0.931269132 0.96181113 0.89164575 0.99878895 1.2263159 1.053418033 0.89164575 0.99878895 1.2263159 0.89164575 0.886735733 0.89164575 1.2263159 0.516547665 1.19743232 1.070646727 0.66449836 0.931269132 1.19743232 1.070646727 0.96181113 0.652091994 0.886735733 1.070646727 1.19743232 1.070646727 1.19743232 0.96181113 0.886735733 out of London out of London 0.89164575 1.3862913 0.836292756 0.957734315 1.19743232 0.516547665 0.516547665 1.19743232 0.69706303 0.868091964 0.516547665 0.66449836 0.767159494 1.1717938 0.886735733 1.19743232 1.070646727 1.1717938 0.836292756 0.66449836 1.070646727 0.516547665 0.886735733 1.070646727 0.516547665

Crystal Palace

Meanwhile Gardens Cantelowes Pollar Hill Victoria Park Clapham Common Crystal Palace Crystal Palace Clapham Common Folkestone Garden Peckham Rye Crystal Palace Bloblands Charlton Mudchute Mile - End Clapham Common Stockwell Mudchute Pollar Hill Bloblands Stockwell Crystal Palace Mile - End Stockwell Crystal Palace Telegraph Hill Crystal Palace Stockwell Bay Sixty 6 Bloblands Victoria Park Bloblands

26.88 26.8 41.33 4.47 11.43 11.56 10.05 2.95 7.13 3 3.32 3.08 1.95 4.84 7.5 4.25 4.76 10.4 2.32 3.21 2.43 1.29 11.4 7.2 6.8 4.57 1.15 5.06 13.48 0.63 13.05 0.38

0.89164575 1.3862913 0.836292756 0.957734315 1.19743232 0.516547665 0.516547665 1.19743232 0.69706303 0.868091964 0.516547665 0.66449836 0.767159494 1.1717938 0.886735733 1.19743232 1.070646727 1.1717938 0.836292756 0.66449836 1.070646727 0.516547665 0.886735733 1.070646727 0.516547665 0.90763183 0.516547665 1.070646727 0.99878895 0.66449836 0.957734315 0.66449836

On the other hand, Mile End, Bay Sixty 6 and Crystal Palace users travel less than 15km to the other locations where they practice skateboarding. Figure 33 illustrates their traces in the city. Comparing figure 32 with figure 33, the preferred locations of the seed users tends to be further from their residences than the wave 1 users’ preferred locations.

Figure 33. Measurement of skateparks’ popularity. Distance from skaters’ houses to nominated skateparks in wave 1. Author.

Figure 34 merged the seed and wave 1 users’ preferred locations. As a general insight from this map, seed users travel longer distances to the skateboarding practice than wave 1 users. Additionally, an additional loyal social group was found – Stockwell users. Out of every ten skaters, six preferred Stockwell among the city’s other skateparks (Table 12).

Figure 34. Measurement of skateparks’ popularity. Distance from skaters’ houses to nominated skateparks in seed and wave 1. Author.

The relationship between travel distances to nominated skateparks and NACH r: n values was also tested Correlation Two (Figure 35). The expectation was that more accessible locations would be correlated with longer travel distances, however, the correlation between the variables was negative (R2 = -0.045) and the sig. (2-tailed) value was greater than 0.05 (P = 0.587), which means that there is a non-significant correlation between the variables. A negative correlation means an inversely proportional relationship: as NACH r: n increases, travel distances decrease. Correlation Two brought the Undercroft twelve times near the regression line as well, a fact that underlines its popularity among the skater community (Table 14).

Figure 35. Correlation between average travel distances from skaters’ residences to nominated skateparks & average NACH r:n of nominated skateparks. Author.

Table 14. The Undercroft highlighted twelve times, nominations near the regression line. Author.

The main findings of this sections correspond to the relationship between longer travel distances with higher NACH r: n values in the interview locations, whereas shorter travel distances are associated with higher NACH r: n values in the nominated locations. Stockwell skatepark was found to be the second location in London with a loyal community and the Undercroft was the most nominated location among the interviewed users.

4.6. Movement pattern snapshots: Mile End skatepark. A study of the movement and the spatial experience of skaters in the most shared practice location (Figure 36), was essential to understanding the interaction of the skater community in skateparks. Mile End was nominated as the most shared location in skateboarding practice.

Interaction patterns, snapshot and movement traces were recorded for five minutes; the forty users that gathered in the skatepark were the characters of the snapshot. The snapshots and traces demonstrated that interaction happens spontaneously; skaters organise themselves harmonically without following any rules. Skaters tend to enjoy their ride, without troubles at the time of skating.

Figures 36, 37, 38 show how the movement patterns inside a skatepark follow a circuit logic which is been defined according to the placement of the infrastructure. Figure 36 shows that the perimeter or external infrastructure of the ring is used for resting, a second ring (from the outside to the inside) is used by beginners, such as S6 and S25, who use the flatland just to roll in the flat floor’s surface and an internal circuit for more experienced users such as S16, S19 and S21. The use of space according to the personal experience of each user has been defined as the main organiser of the user’s distribution in the skatepark. Additionally, the interaction usually happens at the infrastructure edges (Figure 36, users S16, S17, S18).

Figure 36. Movement patterns - Snapshots. Minute 1. Author.

Skaters interact while they are waiting to perform their tricks or after they have done them. Extraordinary support was seen among the skater community before or after their performance. Figure 37 shows the interaction of S2, S6, S30 and S31 after their performance.

Figure 37. Movement patterns - Snapshots. Minute 2. Author.

Figures 36-41 shows the complete spatial function analysis of Mile End after five minutes of the skaters’ performance. Figure 41 overlaid the movement patterns and snapshots of the five minutes recorded. A confluence of interaction in the infrastructure network and the use of the infrastructure according to the degree of experience of the users was highlighted. Additionally, a particular finding was that there weren’t any females skating during the night of the observations, an interesting fact because Mile End represents a shared location of skateboarding practice according to the previous findings. This reinforces the information gathered during the surveys. Table 15 shows female’s skateparks nominations: from fourteen females interviewed, thirteen nominated other skateparks, but Mile End was mentioned by three of the females interviewed (21.24 %). Table 15. Female-nominated skateparks. Author.

Figure 38. Movement patterns - Snapshots. Minute 3. Author.

Figure 39. Movement patterns - Snapshots. Minute 4. Author.

Figure 40. Movement patterns - Snapshots. Minute 5. Author.

Figure 41. Movement pattern snapshots. Overlaid after five minutes. Author.

Gender distribution is not equal in London’s skateparks. However, there are important findings to highlight: community sense, flexible bonding and spontaneous interaction represent the main social patterns carried out in with the spatial function analysis.

The networks of practice of skaters in London provide a picture of the movement of this community in the city. Similarly, the popularity of a location because of the repeated nominations (the Undercroft) as the preferred shared practice location (Mile End) were found. These findings were tested correlating syntactical values of each skatepark with users’ travel distances. The longer trips were associated with the seed locations, while the shortest distances were correlated to skateparks close to the skaters’ houses. In both cases, the Undercroft was founded as a recurrent location; longer distances are travelled to visit it and users’ that live near the Undercroft nominated the location as a place that they frequently practiced the sport.

5. Discussion The use of SNA helped to provide evidence for the hypothesis of Undercroft as the core location of the skateboarding culture in London. Through empirical data gathering and analytical methods, two locations were found to be the most used in London. The Undercroft was the most popular, and Mile End was the preferred shared location of skateboarding practice. Additionally, the use of proximity as the second approach to collect facts in order to discuss how London’s skater community moves around the city overlaid with the previous findings of the SNA method helped to construct the final argument.

Traditional syntax theory would suggest that a place’s popularity would be associated with proximity (Cohen et al., 2007). However, after testing this assumption, two diverse answers were found: in the case of the interview locations, users tend to travel higher distances to more accessible locations with higher NACH r: n values. Users travel an average distance of between 12.48 and 20.10 km to visit accessible locations, such as the House of Vans (NACH r: n 0.9313), the Rom (r: n 1.0907) and the Undercroft (NACH r:n 0.9618). On the other hand, in the case of the nominated locations, shorter distances <15km were travelled by users to accessible locations. The Undercroft was nominated nineteen times. Twelve of these nominations correspond to travel journeys of 3.87–11.26km (NACH r: n 0.9618). This finding suggests that the interviewed locations are skateparks with strong social ties and loyal communities, as in the cases of the Rom and Stockwell, and that the nominated skateparks are practice locations near the users’ residences.

Skatepark infrastructure has a relevant influence as well. Peripheral skateparks are characterised by ramps, whereas parks in the core are characterised by bowls. The flux of users from the periphery to city’s core skateparks can be associated with the spatial practices of skaters in skateparks.

According to Beal, “skateboarding culture creates its own norms and relations that emphasise participant control of the physical activity and open participation rather than competition” (Beal, 1995, p. 254). In the Mile End mapping of social patterns of interaction, Beal’s assumption was confirmed: traces showed different rings of usage according to the users’ experience in a relaxed atmosphere. Likewise, the ring structure can be extrapolated to the metropolitan scale, from a beginner external ring (ramp skateparks), to an intermediate and a final experiment core (bowls skateparks). It was found that the interaction in skateparks is related to the distribution of infrastructure. Usually, interaction takes place around the edges of the skatepark’s infrastructure, when users have finished or started their performances.

Even though skating does not have a formal structure of rules, the power of community in these skateparks represents a reinforcement of the community sense. Hillier’s proposal of virtual community as the physical distribution of people in space (Hillier, 1996) helped the researcher understand the interaction of this social group. In some other sports, freedom in the community performance would mean chaos, whereas in skateboarding, the bonding among the users represents the natural rhythm of the practice. ‘The lack of a formal structure, led to a very flexible environment where the participants not only controlled their own activity but engaged in creativity endeavours’ (Beal, 1995, p. 264)

Furthermore, in terms of gender equality, London’s skateparks users were dominated by men (82.5%). The skateboarding phenomenon in the city is represented by men, however, the House of Vans skatepark and Bay Sixty 6 promote girls-only skating evenings to empower female skaters to increase their participation in the community.

6. Conclusions

The case study of London’s skater community served to empirically analyse their traces around the city and in the skateparks. Space syntax theory, in combination with social network analysis (SNA), constituted the main framework of analysis for this research. This research addressed the networks of practice of this community from the metropolitan scale to the empirical observations in the most shared practice skateparks in London. The complexities behind tracing the movement of a specific social group from the metropolitan scale to the final construction of their traces in their preferred locations was the challenge of this research. The skater community was tracked until the final mapping of their network of practice in the city and their favourite locations of skateboarding practice were found; the interactions at the time of the sport practice were mapped as well.

This research proved, with the use of space syntax and SNA methods, that the selection of the skateparks among the community members is a combination of social bonding, the accessibility of locations and travel distances from the user’s residences. The observations of human behaviour around the spatial practices of the sport can be influenced by the infrastructure. The metropolitan logic of the skatepark’s infrastructure distribution is congruent with its displacement in a specific skatepark.

The study was limited in that surveys were run only in eight of London’s 61 skateparks, additionally, of the 80 interviewed skateparks users not all them answered the complete questionnaire. Moreover, the movement traces were done only in one of the city’s skateparks. The findings, however, provided a snapshot of the current networks of practice of the skater community, their movement in the city and in a skatepark. Future research could consider comparing the traces of skaters in more than one location, to have a general

overview of the users’ performances in accordance with the infrastructure provision.

The main contribution of this research is the methodological development towards the construction of the skater’s social network of practice to achieve the popularity ranking of London’s skatepark from skater’s opinions (the most popular location and shared practice location). The most powerful output of the research is the construction of the network by simply asking where users live and what other skateparks they visit. The adaption and combination of space syntax and SNA methods led to the determination of the most popular location, the preferred shared practice location and the interaction patterns among the skatepark users. This study thus provides a model for the rigorous evaluation of the popularity of any location frequented by a specified social group.

REFERENCES

Bastian, M., Heymann, S. and Jacomy, M., 2009. Gephi: an open source software for exploring and manipulating networks. Icwsm, 8(2009), pp.361-362. Beal, B., 1995. Disqualifying the Official: An Exploration of Social Resistance Through the Subculture of Skateboarding. Sociol. Sport J. 12, 252–267. Biernacki, P., Waldorf, D., 1981. Snowball Sampling: Problems and Techniques of Chain Referral Sampling. Sociol. Methods Res. 10, 141–163. https://doi.org/10.1177/004912418101000205 Borden, I., 2015. The new skate city: how skateboarders are joining the urban mainstream. The Guardian. Borden, I., 2018. Skating and the city a complete history, 2018. ed. Bloomsbury Academic, London. Borden, I., 2014. Skateboarding, space and the city: architecture and the body, reprinted 2014. ed. Bloomsbury Academic, London. Brixton Buzz news, features and listings for Brixton, London, 2018. Stockwell Skatepark listed as an Asset of Community Value in a bid to keep away developers. [online] Available at: http://www.brixtonbuzz.com/2015/01/stockwellskatepark-listed-as-an-asset-of-community-value-in-a-bid-to-keep-awaydevelopers/ [Accessed 2 Sep. 2018]. Brown, M. (2018). The Rom, Hornchurch, becomes first skatepark in Europe to get listed status. [online] the Guardian. Available at: https://www.theguardian.com/culture/2014/oct/29/the-rom-hornchurch-firstskatepark-europe-listed-status [Accessed 29 Aug. 2018]. Bruhn, J.G., 2011. The Sociology of Community Connections. Springer Science & Business Media. Carr, J., 2010. Legal Geographies—Skating Around the Edges of the Law: Urban Skateboarding and the Role of Law in Determining Young Peoples’ Place in the City. Urban Geogr. 31, 988–1003. https://doi.org/10.2747/0272-3638.31.7.988 Christopoulos, D., 2009, February. Peer Esteem Snowballing: A methodology for expert surveys. In Eurostat conference for new techniques and technologies for statistics (pp. 171-179). Cohen, D.A., McKenzie, T.L., Sehgal, A., Williamson, S., Golinelli, D., Lurie, N., 2007. Contribution of Public Parks to Physical Activity. Am. J. Public Health 97, 509–514. https://doi.org/10.2105/AJPH.2005.072447 89

Events Archive - BAYSIXTY6 Skate Park. [online] https://www.baysixty6.com/events/ [Accessed 15 Aug. 2018].

Available

at:

Granovetter, M., 1983. The Strength of Weak Ties: A Network Theory Revisited. Sociol. Theory 1, 201. https://doi.org/10.2307/202051 Han, B., n.d. Reweaving the Fabric: A Theoretical Framework for the Study of the Social and Spatial Networks in the Traditional Neighborhoods in Beijing, China 12. Hillier, B., Hanson, J., 1989. The Social Logic of Space. Cambridge University Press. Hillier, B., Hanson, J., Graham, H., 1987. Ideas are in things: an application of the space syntax method to discovering house genotypes. Environ. Plan. B Plan. Des. 14, 363–385. https://doi.org/10.1068/b140363 Hillier, B., Burdett, R., Peponis, J., Penn, A. (1987), Creating Life: Or, Does Architecture Determine Anything? Architecture et Comportement/Architecture and Behaviour , 3 (3) 233 - 250. pp.237 Hillier, B., Hanson, J., 1984. The Social Logic of Space. Cambridge University Press. Hillier, B., Yang, T., Turner, A., (2012) Advancing depthmap to advance our understanding of cities. In: Greene, M and Reyes, J and Castro, A, (eds.) 8th International Space Syntax Symposium. Pontificia Universidad Catolica de Chile: Santiago, Chile. House of Vans. [online] Available at: http://houseofvanslondon.com/events [Accessed 15 Aug. 2018]. Koohsari, M.J., Kaczynski, A.T., Mcormack, G.R., Sugiyama, T., 2014. Using Space Syntax to Assess the Built Environment for Physical Activity: Applications to Research on Parks and Public Open Spaces. Leis. Sci. 36, 206–216. https://doi.org/10.1080/01490400.2013.856722 Lombard, K.-J., 2015a. Skateboarding: Subcultures, Sites and Shifts. Routledge. Long Live Southbank. [online] Available at: http://www.llsb.com/theproject/ [Accessed 16 Aug. 2018]. Map of skateparks in London - London Skateparks - Guide to skateparks across Greater London [WWW Document], n.d. URL http://www.londonskateparks.co.uk/skateparks-map (accessed 6.16.18). Skateboarding leaps into 2020 Olympics. [online] Available at: https://www.bbc.co.uk/news/av/world-europe-37164307/skateboarding-leapsinto-the-tokyo-2020-olympics [Accessed 15 Aug. 2018]. 90

SNE Architects » Hungerford Bridge, London UK. [online] Available at: http://www.snearchitects.com/project/hungerford-bridge-london-uk-2/ [Accessed 29 Aug. 2018]. Peponis, J., Ross, C., Rashid, M., 1997. The structure of urban space, movement and co-presence: The case of Atlanta. Geoforum 28, 341–358. https://doi.org/10.1016/S0016-7185(97)00016-X Wasserman, S., 1994. Advances in Social Network Analysis: Research in the Social and Behavioral Sciences. SAGE. Wasserman, S., Faust, K., 1994. Social Network Analysis: Methods and Applications. Cambridge University Press. Woolley, H., 2003. Urban Open Spaces. Taylor & Francis.

APPENDIX 1 Pilot’s survey.

APPENDIX 2 Final survey.

APPENDIX 3 Mapped skateparks

CRYSTAL PALACE

CLAPHAM COMMON

BAY SIXTY 6

MILE -END

HOUSE OF VANS

UNDERCROFT

STOCKWELL

ROM

How old are you? 41 - 45 46 + 46 + 41 - 45 46 + 41 - 45 46 + 41 - 45 46 + 41 - 45 26 - 30 21 - 25 21 - 25 26 - 30 21 - 25 26 - 30 16 - 20 26 - 30 26 - 30 31 - 35 26 - 30 16 - 20 26 - 30 21 - 25 16 - 20 26 - 30 26 - 30 16 - 20 16 - 20 21 - 25 21 - 25 16 - 20 16 - 20 16 - 20 16 - 20 21 - 25 26 - 30 16 - 20 21 - 25 21 - 25 21 - 25 16 - 20 16 - 20 16 - 20 16 - 20 21 - 25 26 - 30 16 - 20 16 - 20 21 - 25 16 - 20 21 - 25 26 - 30 41 - 45 16 - 20 21 - 25 26 - 30 21 - 25 21 - 25 21 - 25 21 - 25 21 - 25 21 - 25 41 - 45 21 - 25 16 - 20 26 - 30 26 - 30 21 - 25 21 - 25 16 - 20 21 - 25 21 - 25 21 - 25 16 - 20 31 - 35 16 - 20 41 - 45 16 - 20 21 - 25

How often do you come to skate?

2 times per week 1 time per week 2 times per week Never 2 times per week 3 times per week 3 times per week Never 2 times per week 3 times per week 3 times per week 3 times per week Everyday Everyday 1 time per week 3 times per week 1 time per week 3 times per week 3 times per week 2 times per week 1 time per week 1 time per week Everyday 1 time per week 1 time per week 1 time per month 2 times per week 1 time per week 1 time per week 3 times per week 1 time per week Everyday 2 times per week 2 times per week 1 time per week 1 time per week 1 time per week 1 time per week 2 times per week 1 time per week 4 - 7 times per week 3 times per week 3 times per week 6 times per week 6 times per week 6 times per week 2 times per week 2 times per week 2 times per week 2 times per week 3 times per week 2 times per week 3 times per week 2 times per week 4 times per week 2 times per week 2 times per week 2 times per week 2 times per week 2 times per week 7 times per week 3 times per week 3 times per week twice a month 2 times per week 2 times per week 3 times per week 2 times per week 2 times per week 2 times per week 2 times per week 2 times per week 1 time per week 2 times per week 4, 5 days a week 3 times per week 7 days a week 1 time per week 1 time per week 3 times per week

Male Male Male Male Male Male Male Male Male Male Male Male Female Male Male Male Male Male Male Male Male Male Male Male Male Male Male Female Male Female Female Male Female Male Female Female Female Male Male Male Male Male Male Male Male Male Male Male Male Male Male Male Male Male Male Male Male Female Female Male Male Male Male Male Male Male Female Male Male Female Male Male Female Female Male Male Male Male Male Male

Gender Professional Professional Professional Artist Retired Worker Professional Artist Worker Worker Professional Professional Worker Professional Professional Worker Worker Worker Professional Worker Professional Worker Worker Professional Worker Professional Worker High school student Professional Professional Professional Worker University student University student University student University student Professional Worker University student University student Worker High school student High school student University student University student Worker Professional High school student High school student University student University student Worker Professional Professional University student University student Professional Worker University student University student Worker Worker Worker Professional Worker Worker University student Worker Professional Worker Worker Worker Professional Worker University student Professional University student Professional Worker Worker

What is your profession? Urban Art Practicing skateboarding Practicing skateboarding Urban Art Practicing skateboarding Practicing skateboarding Practicing skateboarding Mural of Rom Skatepark Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Photography Practicing skateboarding Practicing skateboarding Practicing skateboarding General public General public Photography Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding General public Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding Practicing skateboarding

What is the purpose of your visit?

Italy W11 W10 6EF NW1 3FF WA1 95D SE5 W12 W13 W10 W10 SE27 SW198LX E17 SW9 South East SW11 AL1SLM E16 (east) SW19 SW1 SE6 SW2 SE3 SW16 SW2 SE279RE SE27 SE20 SW4 SE6

CM2 RM16 SST Amsterdam 1G9 5QF RM154DG RM138BB Amsterdam TN158FN E63ES SE279LQ SE13 SW9 SE5 SM45JD SW11 SM52AT SE24 SE4 BR31RB SE5 SE1 SG13 HP12 SW15 SE5 SE8 SW11 TW12 KT6 N19 5PX WD17 Stratford Harrow, HA3 Leyton, E105Ps Barking NW8 Dartford, DA1 Brixton West Norwood E3 Limehouse Mile-End E65JG E9 5 RR British Columbia Canada, N8 Dagenham Heathway Barking Area

Where do you live? Chelmsford Rom No No No No Rom No Borough Green Mile - End , Undercroft Yes Deptford Stockwell, Crystal Palace, Undercroft Yes No Deptford No

Do you visit your neighbourhood's skateparks? Please specify

Raw data, questionnaires answers.

Y Cla Y Und

Mile - End Y Crystal

Bar

Do you visit more s

Stockwell, Telegraph Hill, Folkestore Mile Crystal Palace Y No Roy No Crystal Hartham Bowl Clissold Park No Yes Bay 66, No Folkstone Park Und Yes Cla No No Cantelouse Sout Watford, Harrow Mile Mile - end, Victoria Park Y Harrow Skatepark Mile - end, Bay No Sout Mile - end, Cantelowes Mile - end, No Sout No No Southban Stockwell, Clapham Stockwell, Clapham Stockwell, Clap Stockwell, Clapham Common Stockwell, Clapham Common Stockwell, Clapham Co Mile - End Mile - End Victoria Park , Ba Mile - End Mile - End Mile Mile-End Mile-End Mile-End , Mile- End Mile- End Stoc No Victoria Park Victor City Park City Park Finsbury Finsbury Mile No No Mile Barking Barking Victoria Park, U Mile - End Mile - End Mile - End, No No No No Bay Sixty 6 , Meanwhile Gardens Bay Sixty 6 , Meanwhile Gardens Bay Sixty 6 , Me Cantelowes Cantelowes Victor No No Clapham, Stockwell Clapham, Stockwell Clapham, Stockwell, U Meanwhile Gardens , Bay Sixty 6, Royal Oak Meanwhile Gardens , Bay Sixty 6, Royal Oak Und River Brent, Mean While Gardens, Bay Sixty 6, Royal Oak River Brent, Mean While Gardens, Bay Sixty 6, Royal Oak River Brent, Mean While Gar Meanwhile Gardens Meanwhile Gardens Meanwhile Gar Meanwhile Gardens, Royal Oak Meanwhile Gardens, Royal Oak Meanwhile Gar Crystal Palace, Clapham, Stockwell, Bloblands Clapham House of van Clapham Common No Southbank Lloyds Park Lloyds Park Mile Stockwell, Clapham Stockwell, Clapham Stockwell Peckham Rye Peckham Rye Peckh Stockwell Clapham Undercroft Pioneer (indoor park) Cantelowes, Hemel Hempstead , Meanwhile Gardens, Pollard Hill Cantelowes, Hemel Hempstead No Victoria Park Clapham Crystal Palace No Crystal No No Folkestone Park, Crystal Palace Crystal Palace Crystal Bloblands Bloblands Blob Charlton Mudchute Mile Clapham , Stockwell Wandsworth, Clapham, Stockwell Mud Stockwell, Bloblands Stockwell, Bloblands Stockwell, Bloblands, Crystal Palace, Stockwell Yes Bay Sixty 6 Bloblands Bloblands Most in Crystal Palace Park Crystal Palace Mile End No No No No New Cross,

No Rom No Marnixstraat No No Rom Yes Yes No No Stockwell Stockwell, Crystal Palace, Undercroft Stockwell, Crystal Palace Clapham Stockwell Abandoned Bloblands Telegraph Hill Crystal Palace No No Hartham Bowl Yes Yes No Folkstone Park Clapham No No Cantelouse Watford Mile - end, Victoria Park Harrow Skatepark No No

Are there any attractive skateparks in your neighbourhood? Please specify

APPENDIX 4

ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing

ing ing ing ing

ing ing ing

ing ing ing rk ing ing ing ing ing ing ing ing ing ing ing ing ing ing ing

ing ing

your

Italy W11 W10 6EF NW1 3FF WA1 95D SE5 W12 W13 W10 W10 SE27 SW198LX E17 SW9 South East SW11 AL1SLM E16 (east) SW19 SW1 SE6 SW2 SE3 SW16 SW2 SE279RE SE27 SE20 SW4 SE6

Where do you live?

Chelmsford Rom No No No No Rom No Borough Green Mile - End , Undercroft Yes Deptford Stockwell, Crystal Palace, Undercroft Yes No Deptford No

Do you visit more skateparks in London?

Barking No Yes No No Yes No No No Mile - End , Undercroft Yes Crystal Palace No Yes Clapham Yes Undercroft No Stockwell, Telegraph Hill, Folkestore Mile - end Crystal Palace Yes No Royal Oak No Crystal Palace Hartham Bowl Clissold Park, Victoria Park No No Yes Bay 66, Mile - End No No Folkstone Park Undercroft Yes Clapham No No No No Cantelouse Southbank Watford, Harrow Mile - end Mile - end, Victoria Park Yes Harrow Skatepark Mile - end, Bay 6e, Southbank No Southbank Mile - end, Cantelowes Mile - end, Cantelowes No Southbank No No Southbank, Mile- end Stockwell, Clapham Stockwell, Clapham Stockwell, Clapham, Southbank Stockwell, Clapham Common Stockwell, Clapham Common Stockwell, Clapham Common, Bay 66, Southbank Mile - End Mile - End Victoria Park , Bay Sixty 6, Clapham Mile - End Mile - End Mile - End Mile-End Mile-End Mile-End , Undercroft Mile- End Mile- End Stockwell No Victoria Park Victoria Park City Park City Park No Finsbury Finsbury Mile - End No No Mile - End Barking Barking Victoria Park, Undercroft, Barking Mile - End Mile - End Mile - End, Southbank No No No No No No Bay Sixty 6 , Meanwhile Gardens Bay Sixty 6 , Meanwhile Gardens Bay Sixty 6 , Meanwhile Gardens Cantelowes Cantelowes Victoria Park No No No Clapham, Stockwell Clapham, Stockwell Clapham, Stockwell, Undercroft, House of Vans Meanwhile Gardens , Bay Sixty 6, Royal Oak Meanwhile Gardens , Bay Sixty 6, Royal Oak Undercroft River Brent, Mean While Gardens, Bay Sixty 6, Royal Oak River Brent, Mean While Gardens, Bay Sixty 6, Royal Oak River Brent, Mean While Gardens, Bay Sixty 6, Royal Oak Meanwhile Gardens Meanwhile Gardens Meanwhile Gardens, Mile - end Meanwhile Gardens, Royal Oak Meanwhile Gardens, Royal Oak Meanwhile Gardens, Royal Oak Crystal Palace, Clapham, Stockwell, Bloblands Clapham House of vans Street skating Clapham Common No Southbank and Stockwell Lloyds Park Lloyds Park Mile -end Stockwell, Clapham Stockwell, Clapham Stockwell, Clapham Peckham Rye Peckham Rye Peckham Rye Stockwell Clapham Undercroft, Mile - end Pioneer (indoor park) Cantelowes, Hemel Hempstead , Meanwhile Gardens, Pollard Hill Cantelowes, Hemel Hempstead , Meanwhile Gardens, Pollard Hill No Victoria Park Clapham Common Crystal Palace No Crystal Palace No No Folkestone Park, Clapham Common Crystal Palace Crystal Palace Crystal Palace Bloblands Bloblands Bloblands Charlton Mudchute Mile - End Clapham , Stockwell Wandsworth, Clapham, Stockwell Mudchute Stockwell, Bloblands Stockwell, Bloblands Stockwell, Bloblands Bloblands, Crystal Palace, Stockwell Yes Bay Sixty 6 - Victoria Park Bloblands Bloblands Most in South East Crystal Palace Park Crystal Palace Mile End , Stockwell No No No No No New Cross, Telegraph Hill

Do you visit your neighbourhood's skateparks? Please specify

Are there any attractive skateparks in your neighbourhood? Please specify Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Alone Friends Friends Friends Alone Alone Friends Friends Friends Friends Friends Friends Alone Friends Friends Alone Friends Friends Friends Friends Friends Friends Alone Friends Friends Friends Friends Friends Friends Friends Friends Friends Friends Friends Friends Friends Alone Friends Friends Friends Alone Friends Alone Friends Friends Alone Alone Alone Friends Alone Friends Friends Alone Alone Alone Friends Friends Alone Friends Alone Friends Friends Alone Friends Alone Friends Friends Friends Friends Alone Friends Friends Friends Friends Friends Friends

Would you say you have good friends here among the other users?

Friends Friends Friends

Are you normally coming alone or with your friends? No No No Rom No No No No No Rom Friends of Stockwell skatepark Blast Skates No Sidewalk Magazine Yes Yes No No skateparks.co.uk No No No No No No No No No No No No No Harrow Collective , Wodri Harrow Collective Word No No No No No Skate Lessons at Bay Sixty 6 No No No No Bachelor Suite BC Pushing Boarders No No No No No No No Worker and Organiser at Bay Sixty 6 No No No No No No No No No No No No No Royal Oak No No No No No No No Yes Palace Skateboards No Yes

Do you participate in any organisation that promotes skateboarding? Could you please specify

APPENDIX 4

Raw data, questionnaires answers.

APPENDIX 5 One - mode network scheme.

APPENDIX 6 Two - mode network scheme.

APPENDIX 7 Interviews sites and nominations

100

Rolling the city. Tracing skaters’ network of practice in London

Articles inside

4.6. Movement pattern snapshots: Mile End skatepark

4.3. Skatepark–skatepark network of practice (one-mode network

4.2. Skateparks–skaters network of practice (two-mode network

Wave 1

2.1. Brief historical sketch of skateboarding as a practice History of the skateboarding practice and performance interaction of users ..................................................................................................................11

3.1. Mapping skateparks

Patterns of social interaction

4.1.Mapping London’s skateparks infrastructure

Space syntax and accessibility to open spaces

The skater community

Current debate: towards an educational practice