mlsanityData to 14 Oct 2026

Downstream Effects of Affirmative Action

arXiv 1808.09004 ↗First posted 27 Aug 2018cs.GT cs.LG econ.THcited by 34

Not on the map. Why?

Abstract (arXiv)

We study a two-stage model, in which students are 1) admitted to college on the basis of an entrance exam which is a noisy signal about their qualifications (type), and then 2) those students who were admitted to college can be hired by an employer as a function of their college grades, which are an independently drawn noisy signal of their type. Students are drawn from one of two populations, which might have different type distributions. We assume that the employer at the end of the pipeline is rational, in the sense that it computes a posterior distribution on student type conditional on all information that it has available (college admissions, grades, and group membership), and makes a decision based on posterior expectation. We then study what kinds of fairness goals can be achieved by the college by setting its admissions rule and grading policy. For example, the college might have the goal of guaranteeing equal opportunity across populations: that the probability of passing through the pipeline and being hired by the employer should be independent of group membership, conditioned on type. Alternately, the college might have the goal of incentivizing the employer to have a group blind hiring rule. We show that both goals can be achieved when the college does not report grades. On the other hand, we show that under reasonable conditions, these goals are impossible to achieve even in isolation when the college uses an (even minimally) informative grading policy.

Key facts. Cited by 34 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Aug 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 10; 2022: 12; 2023: 6; 2024: 4; 2025: 1; 2026: 1.

34 papers.

Sort:

By area:

  1. 2022Evaluation Gaps in Machine Learning Practicecited by 49
  2. 2021Stateful Strategic Regressioncited by 32
  3. 2023Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairnesscited by 26
  4. 2024Large Language Models as Recommender Systems: A Study of Popularity Biascited by 26
  5. 2021Strategic Rankingcited by 21
  6. 2022Achieving Long-Term Fairness in Sequential Decision Makingcited by 19
  7. 2022What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspectivecited by 18
  8. 2021Multiaccurate Proxies for Downstream Fairnesscited by 17
  9. 2023Fundamental Bounds on Online Strategic Classificationcited by 17
  10. 2022Survey on Fair Reinforcement Learning: Theory and Practicecited by 14
  11. 2021Towards Return Parity in Markov Decision Processescited by 13
  12. 2022The Long Arc of Fairness: Formalisations and Ethical Discoursecited by 13
22 more
  1. 2022Towards Substantive Conceptions of Algorithmic Fairness: Normative Guidance from Equal Opportunity Doctrinescited by 10
  2. 2021Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracingcited by 8
  3. 2022Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipelinecited by 8
  4. 2023Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factorscited by 7
  5. 2024Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Marketscited by 6
  6. 2024Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairnesscited by 6
  7. 2021Precarity: Modeling the Long Term Effects of Compounded Decisions on Individual Instabilitycited by 5
  8. 2021Addressing the Long-term Impact of ML Decisions via Policy Regretcited by 5
  9. 2021Disaggregated Interventions to Reduce Inequalitycited by 5
  10. 2022Counterfactuals for the Futurecited by 5
  11. 2024Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challengescited by 4
  12. 2021Sampling a Near Neighbor in High Dimensions -- Who is the Fairest of Them All?cited by 3
  13. 2022Fairness-Aware Naive Bayes Classifier for Data with Multiple Sensitive Featurescited by 3
  14. 2022Modelling the long-term fairness dynamics of data-driven targeted help on job seekerscited by 2
  15. 2025Counting Hours, Counting Losses: The Toll of Unpredictable Work Schedules on Financial Securitycited by 2
  16. 2021Fair and Optimal Cohort Selection for Linear Utilitiescited by 1
  17. 2022Modeling Human Behavior Part II -- Cognitive approaches and Uncertaintycited by 1
  18. 2023FAIRO: Fairness-aware Adaptation in Sequential-Decision Making for Human-in-the-Loop Systemscited by 1
  19. 2022Offsetting Unequal Competition through RL-assisted Incentive Schemescited by 0
  20. 2023Systemic Fairnesscited by 0
  21. 2023FinA: Fairness of Adverse Effects in Decision-Making of Human-Cyber-Physical-Systemcited by 0
  22. 2026Beyond Outcome Gaps: Process-Aware Fairness Diagnosis for LLM-based Multi-Agent Decision Systemscited by 0