Perceptions and experiences with police among people who use drugs in the initial year of British Columbia's decriminalization of illegal drugs policy
Bibliographic record
Abstract
Abstract Research Summary On January 31, 2023, British Columbia (BC) launched a 3‐year pilot initiative decriminalizing the possession of up to 2.5 g of select illegal drugs. The policy aims to reduce stigma, address racial disparities in drug law enforcement, and improve police relations with people who use drugs (PWUD). As part of a national evaluation, we conducted qualitative interviews with 100 PWUD who reported using drugs at least three times a week across BC between October 2023 and February 2024. Participants, diverse in sociodemographics, drug use patterns, and police interaction histories, largely reported an adversarial relationship with police, marked by historical mistreatment and the targeting of individuals based on aspects of their social identity, such as ethnicity, housing status, and other visible markers. Despite police generally adhering to the policy, some participants reported unlawful drug seizures, reinforcing mistrust. Although some noted reduced fear of police, most felt their negative perceptions persisted post‐decriminalization, highlighting a need for further police education and training to address stigma and inconsistent enforcement. Policy Implications Our findings underscore the need for improved police education and training through better standardization, with an emphasis on promoting consistency and increased transparency, particularly in the use of discretion. Training should also address the impact of systemic racism and discriminatory policing practices to foster equitable interactions with PWUD. Further consideration of alternative nonpunitive legal approaches, alongside expanded harm reduction services, treatment options, social supports (such as housing), and community‐based initiatives, could be highly beneficial. Continued monitoring and evaluation of the policy's impact on PWUD is essential.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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".