Grounded in the matrix of domination of Collins (2009), and drawing on more recent work by Racial Equity Tools (2021) and dRWorksBook (n.d.), we view systemic racism as “the interlocking and reciprocal relationship between the individual, cultural, and institutional levels of racism operate as a system” (Racial Equity Tools, 2021). Usually people associate racism with individuals and in our work we attempt to broaden this perspective to include cultural racism and institutional racism. Systemic racism has been identified as a threshold concept, a concept that is crucial for preservice teachers to broaden their understanding of racism (Winkler, 2018). Our modules seek to simultaneously build statistical literacy, and normalize conversations around race and racism in mathematics and statistics courses. Consistent engagement with these ideas over the long term can foster an understanding of systemic racism. We believe that statistics, with a focus on the aggregate, can help shift the Learners’ focus from individuals to broader systems (Konold & Higgins, 2003). For example, in the traffic stops Learners examine, and seek to explain, patterns across 5000 traffic stops, rather than individual stops.
We draw on Freire’s (2018, 2021) notion of generative themes and Culture Circles, critical statistical literacy (Weiland, 2017), and the GAISE II recommendations (Bargagliotti et al., 2020) to design the statistical investigations. Systemic racism forms our generative theme, coded in the dataset, which Learners’ unpack through their investigation and dialogue with each other and the instructor. In our design approach we modify the proposed statistical investigation from the GAISE framework (formulate statistical investigative questions, collect/consider the data, analyze the data, and interpret the results) to infuse the context of systemic racism in all the elements of an investigation. For example, in considering the data, Learners have opportunities to discuss the variable of race through the Census categories over time.
Figure 1. Modified GAISE investigative model
To codify systemic racism we use real data in contexts where disparities are observed for Black people (e.g., traffic stops, school discipline). In the United States, racial inequalities exist by any measure: wealth, income, health and life expectancy, housing, access to education, encounters with law enforcement and the judicial system, and many others. Thus, any of these contexts can be suitable for the design of modules that will center dialogue around systemic racism.
This project is funded by the National Science Foundation, grant # 2121364. Any opinions, findings, and conclusions or recommendations expressed in these materials are those of the authors and do not necessarily reflect the views of the National Science Foundation.
