The impact of Housing First participation on police-reported crime and crime severity
Bibliographic record
Abstract
Housing First (HF) addresses chronic homelessness by admitting individuals into permanent shelter regardless of their situation. Studies using self-reported data suggest that HF can potentially decrease justice system use, but they are limited by inaccurate measurement of police contacts. This study uses administrative data from police to measure the change in number of police interactions, change in average crime weight (or importance of crime), and change in the distribution of crime weight, before and after HF. Six hundred and two chronically homeless individuals with a history of criminal involvement and who were accommodated by an HF shelter between three months to a year were eligible for this study. We use unconditional quantile regression to observe HF’s effect on changes in the distribution of crime weights over time. While the average crime weight increased during the study period (57–79.1), the average number of police interactions decreased. Statistically significant decreases of approximately 5 crime weight units were observed between percentiles 0.54 and 0.65 and decreases of approximately 15 crime weight units occurred at percentiles 0.73 and 0.81. HF is effective at reducing minor crimes at the highest end of the distribution and helping those experiencing homelessness to avoid the warrant cycle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".