{
  "id": 18733,
  "url": "https://arxiv.org/abs/2509.15122",
  "title": "Prestige over merit: An adapted audit of LLM bias in peer review",
  "summary": "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",
  "authors": "Anthony Howell, Jieshu Wang, Luyu Du, Julia Melkers, Varshil Shah",
  "category": "research",
  "topics": "bias-fairness,transparency,biotech",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-13T04:00:00.000Z",
  "fetched_at": "2026-08-13T05:10:37.786Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/18733",
  "original_url": "https://arxiv.org/abs/2509.15122",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}