Using Fine-Tuned LLMs to Identify Indicators of Vulnerability in UK Police Incident Logs
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
Record details
Published: 22 July 2026
Source: arXiv cs.CY
Category: Research
Topics: Healthcare
Retrieved: 22 July 2026
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ethics.ai (22 July 2026), “Using Fine-Tuned LLMs to Identify Indicators of Vulnerability in UK Police Incident Logs,” evidence record 12290, https://ethics.ai/record/12290 (originally published by arXiv cs.CY).
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