Theories of Statistical Discrimination and Affirmative Action: A Survey

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Fairness in Machine Learning: Lessons from Political Philosophy (2017, background): “Where analytic philosophy ends, sociology, history, economics, and other nascent disciplines are needed, to understand the specific ways in which some groups come to be unfairly disadvantaged Fang and Moro (2010); Hooks (1992). Only then can we meaningfully evaluate whether and to what extent a give”
Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability (2018, result): “Our results also have connections with early economic models on discrimination (see [12] for a review and references).”
Drivers of Gendered Sectoral and Occupational Segregation in Developing Countries (2020, background): “…and occupations where such interruptions are less damaging to employers, typically in jobs and sectors with few career advancement opportunities (Fang and Moro 2010).2 Institutionalist segmented labor market theories argue that labor markets are divided, often into dual “primary” and…”
A multidisciplinary survey on discrimination analysis (2013, background): “A survey by Fang and Moro (2010) reviews theoretical models of statistical discrimination and affirmative actions.”