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Incentives to Offer Algorithmic Recourse

arxiv.org/abs/2301.12884

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Updated 2 h ago · first seen 11 Sept 2026

paper_01M294GPCR19REVGSCT4TAV95R

Published
11 Sept 2026
T1 · 2 h ago
arXiv
2301.12884
T1 · 2 h ago
Category
cs.GT
T1 · 2 h ago

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9 claims · 9 properties

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https://arxiv.org/abs/2301.12884currentcurrentarXiv (Atom API + RSS)T1highdeterministic

Abstractabstract1

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-cross Abstract: Algorithmic recourse promises to help applicants rejected by automated systems by explaining the changes needed to secure acceptance. What incentive do decision-makers, such as banks and employers, have to offer recourse? We study this question in a screening model in which recourse is both productive and selective: completing recourse improves an applicant's value to the decision-maker, but applicants differ in their cost of completion. The optimal policy is a threshold rule: reject applicants with low scores, offer recourse to an intermediate range of scores, and accept applicants with high scores outright. Because the intermediate range spans the cutoff that would separate acceptance from rejection when recourse is not available, some marginal applicants gain a new path to acceptance, while others---who would have been accepted outright---must now clear a costly hurdle.currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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replacecurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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2301.12884currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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Matthew Olckers, Toby WalshcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.GT, cs.AIcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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https://arxiv.org/pdf/2301.12884currentcurrentarXiv (Atom API + RSS)T1highdeterministic

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cs.GTcurrentcurrentarXiv (Atom API + RSS)T1highdeterministic

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11 Sept 2026currentcurrentarXiv (Atom API + RSS)T1highdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →