{
  "id": 7654,
  "url": "https://arxiv.org/abs/2603.05189v2",
  "title": "Small Changes, Big Impact: Demographic Bias in LLM-Based Hiring Through Subtle Sociocultural Markers in Anonymised Resumes",
  "summary": "Large Language Models (LLMs) are increasingly deployed in resume screening pipelines. Although explicit PII (e.g., names) is commonly redacted, resumes typically retain subtle sociocultural markers (languages, co-curricular activities, volunteering, hobbies) that can act as demographic proxies. We introduce a generalisable stress-test framework for hiring fairness instantiated in the Singapore context: 100 neutral job-aligned resumes are augmented into 4100 variants spanning four ethnicities and",
  "authors": "Bryan Chen Zhengyu Tan, Shaun Khoo, Bich Ngoc Doan, Zhengyuan Liu, Nancy F. Chen, Roy Ka-Wei Lee",
  "category": "research",
  "topics": "bias-fairness,jobs-economy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-05T13:58:07.000Z",
  "fetched_at": "2026-07-14T16:33:21.052Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7654",
  "original_url": "https://arxiv.org/abs/2603.05189v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}