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<p>Persistent workplace inequality remains even as explicit demographic prejudice declines and antidiscrimination norms strengthen. This paper introduces the Taste-Based Statistical Discrimination (TBSD) framework to explain this phenomenon. TBSD describes how decision-makers convert observable demographic cues—such as race, gender, accent, attire, or alma mater—into inferences about non-performance-related social identities (e.g., political ideology, cultural values). Subsequently, they enact taste-based animus toward those inferred identities. TBSD operates through a two-stage, moderated process. Stage 1 involves Bayesian-like belief updating, where demographic signals prompt probabilistic attributions of hidden identities. Stage 2 activates affective and evaluative bias against the inferred identity, driving discriminatory behaviors often cloaked as considerations of “cultural fit” or “value alignment.” This paper situates TBSD at the intersection of economic models of taste-based and statistical discrimination and social-cognitive theories of categorization and affective polarization, using partisan sorting as an illustrative test case. Key moderators are identified—including cue diagnosticity, cue ambiguity, evaluator characteristics, situational context, and intersectional cue combinations—that determine when and how TBSD emerges. The framework reconciles the paradox of enduring inequality amid waning explicit prejudice. It also highlights the ethical imperative and managerial challenges of addressing partisan and other covert forms of discrimination. The paper concludes by outlining an empirical agenda spanning experimental, field, and multi-level designs to validate TBSD and inform interventions that promote authentic demographic and ideological inclusion.</p>

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Taste-Based Statistical Discrimination: A New Framework for Understanding Organizational Inequality in a Polarized Era

  • 期刊论文

  • 发表日期：

    2025年8月25日

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  • Lemaro Thompson

摘要

Persistent workplace inequality remains even as explicit demographic prejudice declines and antidiscrimination norms strengthen. This paper introduces the Taste-Based Statistical Discrimination (TBSD) framework to explain this phenomenon. TBSD describes how decision-makers convert observable demographic cues—such as race, gender, accent, attire, or alma mater—into inferences about non-performance-related social identities (e.g., political ideology, cultural values). Subsequently, they enact taste-based animus toward those inferred identities. TBSD operates through a two-stage, moderated process. Stage 1 involves Bayesian-like belief updating, where demographic signals prompt probabilistic attributions of hidden identities. Stage 2 activates affective and evaluative bias against the inferred identity, driving discriminatory behaviors often cloaked as considerations of “cultural fit” or “value alignment.” This paper situates TBSD at the intersection of economic models of taste-based and statistical discrimination and social-cognitive theories of categorization and affective polarization, using partisan sorting as an illustrative test case. Key moderators are identified—including cue diagnosticity, cue ambiguity, evaluator characteristics, situational context, and intersectional cue combinations—that determine when and how TBSD emerges. The framework reconciles the paradox of enduring inequality amid waning explicit prejudice. It also highlights the ethical imperative and managerial challenges of addressing partisan and other covert forms of discrimination. The paper concludes by outlining an empirical agenda spanning experimental, field, and multi-level designs to validate TBSD and inform interventions that promote authentic demographic and ideological inclusion.