Reckoning with statistics' eugenicist origins: Intersectional MAIHDA and the queering of quantitative methods.

Today, we often use our statistical toolset in service of very different aims than their eugenicist creators might have intended, including to document intersectional inequities and to advocate for the correction of injustices. However, lingering eugenicist assumptions may subtly shape how we structure quantitative investigations of group differences. In this commentary, we trace one such assumption and illustrate how this leads to a missed opportunity in our analyses, namely, to expand diversity and inclusion while maintaining robustness of predictions. A relatively new approach, Intersectional MAIHDA (multilevel analysis of individual heterogeneity and discriminatory accuracy), may help to address this. The emerging literature on Intersectional MAIHDA (also called I-MAIHDA) has focused primarily on demonstrating its methodological advantages over conventional quantitative approaches, its alignment with intersectionality theory, and its potential for useful applications in the health and social sciences. In this article, we explore two underappreciated aspects of the approach: (1) Intersectional MAIHDA's alignment with queer theory, and consequently its potential for advancing the project of queering quantitative methods. And (2), that MAIHDA constitutes a radical departure from past practices, and it is this departure that enables its comparative advantages over conventional methods.