Evaluating the association of transferring governance of correctional health care services with overdose and all-cause mortality: a retrospective cohort study in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: In many jurisdictions world-wide, the government agency that manages prisons also provides prison health care services. However, the World Health Organization (WHO) and United Nations (UN) have recommended that health ministries provide prison health care. In Canada, the province of British Columbia (BC) transferred responsibility for correctional health services to the health ministry in accordance with this guidance. The objective of this study was to estimate the association between the transfer in BC and all-cause and overdose mortality within 1 year of release from prison. METHODS: We used a retrospective cohort study design employing the difference-in-differences (DiD) method to compare mortality among formerly-incarcerated people in the pre- and post-transfer periods against a matched community control group to control for province-wide trends in mortality. The data source was a longitudinal linkage of administrative databases. The DiD effect was estimated with survival time-to-event models. RESULTS: In the formerly-incarcerated group (N = 6912), all-cause (3.7% vs 2.6%) and overdose (2.7% vs 1.7%) mortality in the first-year post-release decreased from the pre-transfer period to the post-transfer period, while mortality risk changed little in the community control group (N = 6881) during this time period (all-cause: 0.7% vs 0.9%; overdose: 0.4% vs 0.4%). The transfer was associated with statistically significant reductions in the hazards of all-cause mortality (DiD HR: 0.52, 95% CI: [0.32, 0.83]) and overdose mortality (DiD HR: 0.51, 95% CI: [0.26, 0.99]) in the first-year post-release. CONCLUSIONS: This study provides empirical evidence in support of WHO and UN guidance and indicates that the delivery of correctional health services by community health authorities may reduce deaths, particularly overdose deaths, among people released from correctional centres.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".