The Theory of Discrimination

By Kenneth J. Arrow. 1971

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Citations in the corpus

Efficient candidate screening under multiple tests and implications for fairness (2019, background): “Many subsequent works extend this analysis, typically focusing on Gaussian models of worker quality and conditionally-Gaussian test scores [2, 1].”
A Short-term Intervention for Long-term Fairness in the Labor Market (2017, background): “The theory of statistical discrimination, originally set forth in two seminal papers by Phelps [4] and Arrow [5], explains disparate group outcomes as the result of rational agent behaviors that lock a system into an unfavorable equilibrium.”
The Problem of Infra-marginality in Outcome Tests for Discrimination (2016, background): “The hit rate (i.e., the search 1Taste-based discrimination stands in contrast to statistical discrimination (Arrow, 1973; Phelps, 1972), in which officers might use a driver’s race to improve their estimate that he is carrying contraband.”
Field Experiments on Discrimination (2016, background): “How could differential beliefs about their abilities persist? One explanation is that employers’ beliefs that minorities are on average less productive are self-reinforcing (Arrow, 1973; Coate and Loury, 1993). This could happen for two reasons. First, minority and majority workers may rationally ma”
Pretrained AI Models: Performativity, Mobility, and Change (2019, background): “That is, as noted in classical economic theories of discrimination [4, 17, 84] and recent models of model retraining [22, 33, 67], populations might become more like what (biased) models predict.”
Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability (2018, unknown): “[2] and [33]).”
Orchestrating Impartiality: The Impact of “Blind” Auditions on Female Musicians (2000, background): “The empirical literature on discrimination, deriving from the seminal contributions of Gary Becker (1971) and Kenneth Arrow (1973), has focused mainly on disparities in earnings be-tween groups (e.g., males and females), given differences in observable productivity-altering characteristics.”
From Fair Decision Making To Social Equality (2018, background): “On the economics side, a large literature exists examining statistical discrimination, dating back to Arrow [2].”
Predictably Unequal? The Effects of Machine Learning on Credit Markets (2020, unknown): “(14)See Fang and Moro (2010) for an excellent survey, as well as classic references on the topic, including Phelps (1972) and Arrow (1973).”
Women and Power: Unpopular, Unwilling, or Held Back? (2015, background): “, 2009).(2) This literature has focused mainly on the policy outcomes of female elected leaders, the e ects of quotas on the number of elected women, or the change in attitudes toward women once they are elected, and not on the intrinsic theories that could account for women's underrepresentation.”