Evidence record 18714 · automatically gathered

The Accuracy Trap: Structural Scarcity Amplifies Relative Inequality in Algorithmic Allocation

arXiv:2608.11491v1 Announce Type: new Abstract: Algorithmic systems increasingly rank individuals for access to scarce public resources, from child welfare interventions to cancer treatment referrals. The prevailing fairness frame treats disparity as a property of biased data or deficient models, with remedies through calibration and debiasing. Under structural scarcity, where demand exceeds supply by an order of magnitude, allocation becomes a rationing problem, and the statistical properties o

Record details

Published: 13 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Bias & fairness · Children & education
Retrieved: 13 August 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

How to cite this record

ethics.ai (13 August 2026), “The Accuracy Trap: Structural Scarcity Amplifies Relative Inequality in Algorithmic Allocation,” evidence record 18714, https://ethics.ai/record/18714 (originally published by arXiv cs.CY).

JSON

Use and limitations

This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.