Intersectional synergies: untangling irreducible effects of intersecting identities via information decomposition
Thomas F. Varley, Patrick Kaminski

TL;DR
This paper demonstrates that information theory can empirically detect irreducible intersectional effects in social data, revealing joint effects of identities like race and sex on outcomes that traditional methods fail to distinguish.
Contribution
It introduces an information-theoretic approach to identify and differentiate true synergistic intersectional effects from redundant interactions in empirical data.
Findings
Robust statistical synergies of identities on outcomes are observed.
Linear regression with interaction terms fails to distinguish true synergy from redundancy.
Information theory effectively captures nonlinear, higher-order social dynamics.
Abstract
The idea of intersectionality has become a frequent topic of discussion both in academic sociology, as well as among popular movements for social justice such as Black Lives Matter, intersectional feminism, and LGBT rights. Intersectionality proposes that an individual's experience of society has aspects that are irreducible to the sum of one's various identities considered individually, but are "greater than the sum of their parts." In this work, we show that the effects of intersectional identities can be statistically observed in empirical data using information theory. We show that, when considering the predictive relationship between various identities categories such as race, sex, and income (as a proxy for class) on outcomes such as health and wellness, robust statistical synergies appear. These synergies show that there are joint-effects of identities on outcomes that are…
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Taxonomy
TopicsIncome, Poverty, and Inequality · Psychological Well-being and Life Satisfaction · Mental Health Research Topics
