Introduction
5
deal of damage to the potential of young people. While explicit biases are just as destructive, they tend to be easier to identify and address, whereas implicit biases are, by their nature, more unrecognized, often based on stereotypes and assumptions that the individual and collective community don’t even realize they’re making. As a result, many educators see bias as something other teachers have, but have difficulty recognizing it in their own practices. This makes implicit bias particularly difficult to deconstruct, while its impact is just as negative for students as more explicit bias.
Certainly, we have examples of students who thrived despite such experiences with educator bias, like Mae Jemison’s insistence that she would become a scientist when told by her White kindergarten teacher that she should strive to become a nurse instead (as cited in Changing the Face of Medicine, n.d.). We know from her work that Dr. Jemison went on to become not just a doctor but the first female African American astronaut in history (Changing the Face of Medicine, n.d.). Sadly, the stories we never hear are of the countless students who give up along the way, who believe the limited perspective of the adults who educate them, the stories of students who never strive for more because they’ve been told it’s impossible, or because some element of their circumstances suggests such aspirations are unrealistic. This is where the landscape model of learning comes in.
©️2022 by Solution Tree Press
We see these impacts in many forms, several of which will be explored more deeply later in this book. Research finds that negative stereotypes, such as the behavioral and cultural assumptions that lead to disproportionally higher rates of suspension for African American boys in U.S. schools, can be incredibly damaging, with Black boys perceived as “violent” in cases where White boys are viewed as “having a bad day” for the same behavior (Mills College, 2020). Even positive stereotypes, such as the assumption that Asian Americans are academically high achieving, can cause undue pressure on Asian students of all ages, ignoring students’ unique needs and selves. Research also finds that implicit biases connected to gender negatively affect girls, particularly in mathematics outcomes, and that Black girls are disproportionally penalized for being assertive in the classroom as compared to their White counterparts (Chemaly, 2015). As Mills College (2020) asserts, “Whatever the stereotype, viewing students as a group instead of as individuals leaves them at risk for not getting the support they need to learn.” Whether because of students’ cognitive challenges, exceptional giftedness, cultural identity, race, gender identity, sexual orientation, or socioeconomic background, educators’ implicit biases, however unintentional, often limit students’ goals and, in doing so, cut short potential careers and futures.
