Associations between methadone maintenance treatment and crime: a 17‐year longitudinal cohort study of Canadian provincial offenders
Bibliographic record
Abstract
AIMS: To estimate and test the difference in rates of violent and non-violent crime during medicated and non-medicated methadone treatment episodes. DESIGN, SETTING AND PARTICIPANTS: The study involved linkage of population level administrative data (health and justice) for all individuals (n = 14 530) in British Columbia, Canada with a history of conviction and who filled a methadone prescription between 1 January 1998 and 31 March 2015. Methadone maintenance treatment was the primary independent variable and was treated as a time-varying exposure. Each participant's follow-up (mean: 8 years) was divided into medicated (methadone was dispensed) and non-medicated (methadone was not dispensed) periods with mean durations of 3.3 and 4.6 years, respectively. MEASUREMENTS: Socio-demographics of participants were examined along with the main outcomes of violent and non-violent offences. FINDINGS: During the first 2 years of treatment (≤ 2.0 years), periods in which methadone was dispensed were associated with a 33% lower rate of violent crime [0.67 adjusted hazard ratio (AHR), 95% confidence intervals (CI) = 0.59, 0.76] and a 35% lower rate of non-violent crime (0.65 AHR, 95% CI = 0.62, 0.69) compared with non-medicated periods. This equates to a risk difference of 3.6 (95% CI = 2.6, 4.4) and 37.2 (95% CI = 33.0, 40.4) fewer violent and non-violent offences per 100 person-years, respectively. Significant but smaller protective effects of dispensed methadone were observed across longer treatment intervals (2.0 to ≤ 5.0 years, 5.0 to ≤ 10.0 years). CONCLUSIONS: Among a cohort of Canadian offenders, rates of violent and non-violent offending were lower during periods when individuals were dispensed methadone compared with periods in which they were not dispensed methadone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".