From intersectional invisibility to visibility: Black women in Health Disparity Data and Quantitative Intersectional Models

Abstract

Intersectionality, in its original conceptualization, asserted that the combination of categories can lead to unknown experiences and to invisibility. Over time, to capture the effects which explain Black women's intersectional experiences, quantitative operationalizations of intersectionality made two changes to the concept: first, they reformulated intersectionality to a known difference in outcomes such as health status; second, they began to measure how groups experience such differences under the effect of particular categories. In this paper we demonstrate that, despite these methodological reformulations, intersectionality as invisibility still manifests in quantitative health modelling, thereby not capturing Black women's unique experiences. We use the U.S. 1972–2022 integrated General Social Survey data and the overall self-rated heath, race, and gender variables. We, step by step, outline how intersectional invisibility arises in additive, interactive, and multiplicative models with White male, or the most dominant group, set as the intercept. To visibilize Black women's experience we propose changing the intercept to Black female.