The opioid crisis as health crisis, not criminal crisis : implications for the criminal justice system
Bibliographic record
Abstract
The criminal justice system’s response to the opioid crisis exacerbates risks faced by people using drugs and is harmful to public health. Through a literature review, caselaw analysis, and key-informant interviews in the Greater Vancouver area, this thesis analyzes elements of the criminal justice system’s response to the opioid crisis and provides recommendations to reduce harms experienced by people who use drugs and to promote community health and safety. An analysis of the British Columbia fentanyl trafficking sentencing decisions reveals that courts are emphasizing the need for enhanced deterrence as a response to the fentanyl crisis. In the street-level trafficking cases examined, 12 of the 14 people were motivated to traffic in order to support their own addiction. Interviews with 11 people including defence counsel, probation officers, and public interest lawyers and advocates, revealed challenges of working in the criminal justice system during the opioid crisis. Advocates described the main barrier as a fundamental misunderstanding of addiction within the criminal justice system. Advocates shared their insights into ways the criminal justice system can improve its approach. The key recommendation was for actors and policies within the criminal justice system to begin understanding the opioid crisis as a public health crisis and not a criminal crisis. A review of the literature reveals that lengthening custodial sentences for people who are trafficking fentanyl will not deter street-level trafficking. Instead, the court’s punitive approach will increase the number of individuals in custody, and disproportionately impact Indigenous people and those with substance abuse issues. Evidence-based harm reduction practices can be implemented in the justice system to reduce harm, from bail orders to prison conditions. There is a strong need for more rehabilitative options, community supports, and diversion opportunities to address the overrepresentation of people who use substances within custody.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.025 | 0.031 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".