  An interactionist version of structuralism can incorporate research on prejudice into a wider understanding of inequity, rather than eschew it. One way to do so is to identify ways in which psychological biases (whether implicit or explicit) might be key contributors to social-structural phenomena. For example, structuralists sometimes point to the drug laws and sentencing guidelines that contribute to the mass incarceration of black men in the USA as examples of systemic biases. Sometimes, however, when these laws and policies change, discrimination persists. While arrests have declined for all racial groups in states that have decriminalized marijuana, black people continue to be arrested for marijuana-related offenses at a rate of about 10 times that of white people (Drug Policy Alliance 2018). This suggests that psychological biases (belonging to officers, policy makers, or voters) are an ineliminable part of systemic inequity. Such interactionism is just one approach for blending individual and institutional approaches to intergroup discrimination (see, e.g., Madva 2016a, 2017; Davidson &amp; Kelly forthcoming). Another idea is to incorporate research specifically on implicit bias into a wider understanding of the structural sources of inequity by using implicit measures to assess broad social patterns (rather than to assess the differences between individuals). The “Bias of Crowds” model (§2.5) argues that implicit bias is a feature of cultures and communities. For example, average scores on implicit measures of prejudice and stereotypes, when aggregated at the level of cities within the United States, predict racial disparities of shootings of citizens by police in those cities (Hehman et al. 2017). Thus, while it is certainly true that most of the relevant literature and discussion conceptualizes implicit bias as way of differentiating between individuals, structuralists might utilize the data for differentiating regions, cultures, and so on.