{
  "id": 12290,
  "url": "https://arxiv.org/abs/2607.18446",
  "title": "Using Fine-Tuned LLMs to Identify Indicators of Vulnerability in UK Police Incident Logs",
  "summary": "arXiv:2607.18446v1 Announce Type: cross Abstract: Purpose: Understanding how much of routine policing involves vulnerable people could inform resourcing, training, and multi-agency response, yet administrative data provide limited insight. We explore whether an LLM-based classification pipeline, developed on open-source US police data, can be adapted to estimate the prevalence of four vulnerability indicators - mental ill health, substance misuse, alcohol dependence, and homelessness - in UK pol",
  "authors": "Sam Relins, Daniel Birks",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": "uk",
  "published_at": "2026-07-22T04:00:00.000Z",
  "fetched_at": "2026-07-22T05:10:49.469Z",
  "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/12290",
  "original_url": "https://arxiv.org/abs/2607.18446",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}