Evidence record 12290 · automatically gathered

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

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

How to cite this record

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).

JSON

Use and limitations

This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.