Queering Quantitative Methodology Teaching for Intersectional Justice

• In Event: Teaching Critical Quantitative Methods in Higher Education

Abstract

In this paper, I share from my experiences as a queer scholar (both identifying as queer as an individual and engaging queer and trans theories and methods in my scholarship) teaching quantitative methodology instruction across three public universities in the Southeast. I teach across the quantitative methods curriculum, including introduction to statistics courses through advanced multivariate and measurement courses over the course of a decade. I have also written several statistics textbooks (Author 2019, Author 2020, Author 2021). My own journey toward teaching quantitative methodologies queerly and with an intersectional eye has taken time. I was trained in a very traditional manner by very deeply positivist professors and mentors, and carried much of that approach into my own initial teaching approach. For the first couple of years, I separated my teaching (which remained traditionalist and positivist) from my scholarship. I incorporated harm-reduction strategies such as being thoughtful about examples that reinforced binary notions of gender (e.g., using men/women as examples for two-group analyses) or racist stereotypes (e.g., achievement gaps).

Over time, more critical approaches to quantitative methodologies emerged such as queer quantitative inquiry (e.g., Garvey, 2007) and QuantCrit (e.g., Garcia et al., 2017) that provided new ways of thinking about statistical methodologies and spurred me to re-evaluate my own teaching. Initially, I added units to courses to fold in critical methodologies, primarily positioning those after traditional methods in the course calendar. Then, over the course of three years, I redesigned the entire quantitative methods sequence to be a “critical-first” model. In this paper, I will discuss some of the lessons I have learned from that process, as well as some directions that I hope will be helpful to others seeking to teach quantitative methodologies and statistics more critically.

Moving to a critical-first approach was key in gaining student buy-in and scaffolding future learning of traditional approaches. For example, starting the first week of introductory-level quantitative methods courses with an overview of the history of quantitative methodologies has been beneficial. We begin with an examination of the roots of quantitative methods in eugenics and white supremacy (e.g., Bonilla-Silva, 2008; Zuberi, 2001), and an examination of the involvement of quantitative methodologies in the pathologization and illegalization of queer and trans bodies in the U.S. (Terry, 1999). We then move to a unit on the philosophy of science, helping students better disentangle positivism and how it ‘looks’ in methodology as compared with interpretivist, critical, and post-structural approaches. This helps frame larger discussions about features like the assumptions of the general linear model, where they come from, and how they may or may not apply to critical work. When we learn various designs and analyses, we also read case studies of critical quantitative approaches in action. We collectively question and ‘queer’ the foundations of quantitative methodologies, which provides a vehicle both for deeply learning traditional approaches while simultaneously deconstructing and reimagining them.

Author

• Kamden Strunk, Virginia Commonwealth University