{
  "id": 19185,
  "url": "https://arxiv.org/abs/2608.13022v1",
  "title": "Applied and Filtered: An End-to-End Algorithmic Fairness Audit of A Public Employment Agency",
  "summary": "Algorithmic fairness evaluation commonly assesses AI systems as bounded technical components, abstracting away the organizational context in which they operate. We present, to our knowledge, the first independent end-to-end fairness audit of a semi-automated hiring system operated by Barcelona Activa, a public employment agency using the third-party TalentClue platform for candidate search and shortlisting. We analyze approximately 497,000 candidate-vacancy pipeline entries from September 2017 t",
  "authors": "Gemma Galdón-Clavell",
  "category": "research",
  "topics": "bias-fairness,jobs-economy,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-13T09:46:27.000Z",
  "fetched_at": "2026-08-14T05:10:49.168Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/19185",
  "original_url": "https://arxiv.org/abs/2608.13022v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}