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Evidence record 18733 · automatically gathered

Prestige over merit: An adapted audit of LLM bias in peer review

arXiv:2509.15122v2 Announce Type: replace Abstract: Large language models (LLMs) play a growing but largely informal role in scholarly peer review. Yet whether LLMs reproduce biases observed in human decision-making remains unclear. We adapt a resume-style audit to scientific publishing, developing a multi-role LLM simulation (editor/reviewer) that evaluates high-quality manuscripts across the physical, biological, and social sciences under randomized author identities (institutional prestige, g

Record details

Published: 13 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Bias & fairness · Transparency · Biotech
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.

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How to cite this record

ethics.ai (13 August 2026), “Prestige over merit: An adapted audit of LLM bias in peer review,” evidence record 18733, https://ethics.ai/record/18733 (originally published by arXiv cs.CY).

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