Flipping the Script: Teaching How to Use Numbers for Justice

• In Event: Teaching Critical Quantitative Methods in Higher Education

Abstract

While much has been written on QuantCrit and its application in research, there remains a void on how to integrate QuantCrit into the teaching of statistics and other quantitative courses. This paper is a reflection of promising practices one Latina professor has used to engage students and integrate QuantCrit into her econometrics graduate-level course at a prestigious predominately white institution.

Quantitative Critical Race Theory (QuantCrit) is a rapidly emerging field of study seeking to challenge and improve the use of statistical data in social research. It pulls lessons and insights from Critical Race Theory and applies them to understanding social challenges by using quantitative data (Gillborn et al., 2018). Applying QuantCrit means reckoning with the racist structures that have existed and exist, and examining your role in them (Garcia et al., 2018) to transform your research practice in the service of more informed, racially conscious, and equitable ways (Castillo & Gillborn, 2022).

My goal for the econometrics course is for students to become critical consumers of data and research with the understanding that it exists within racist systems. The purpose of the first lesson is to reckon with the racist use of data, then rectify it by flipping the script and using data for justice. The first lecture includes a history of numbers and the eugenic origins of statistics and finishes with the introduction of QuantCrit as a framework for critical analysis. Its core tenets are explained and how to apply them in quantitative research. During the same first lecture, students engage with their own positionality and power in society during turn and talks with their peers.

For the remainder of the course QuantCrit is an integrated core component rather than an afterthought add-on. Every memo (which has a data analysis component) has a required positionality statement where students write about their direct experience and potential bias with the topic they are researching. This past year, I posted pictures of the authors for papers we read. I recognize that identity is multi-dimensional, and a picture is one limited snapshot. Nonetheless, this practice brought to everyone’s attention that although I tried to include more scholars of color in my syllabus, it was clearly not enough since most papers were written by white men, even those about police shootings.

Although ratings, like all data, are biased especially for women of color (MacNell et al., 2015), my course received ratings above the department average and specifically students rated it much higher in the following “contribution of this course to improvement of your capacity for critical evaluation of the subject.”

We are all iterating on how to best teach quantitative courses more equitably. There is no “right” way to teach quantitative material. But we do know that the current “business as usual” approach of not acknowledging the racist past of statistics nor the biases of numbers will only perpetuate the status quo, white supremacy. These promising practices are intended to serve as starting points for faculty to rectify their pedagogy of teaching statistics and specifically advocate for them to use numbers for justice.

Author

• Wendy Castillo, Montclair State University