Harm reduction in policing: responding to persons under the influence of illicit drugs
Bibliographic record
Abstract
The Public Health Agency of Canada estimates between 75,000 and 125,000 injection drug users are addicted to drugs that include heroin, cocaine or amphetamines. Over fifteen thousand drug users are estimated to reside in the Greater Vancouver area; 69% have reported sharing needles. The Greater Vancouver region, with special consideration for the Downtown Vancouver Eastside, Canada's poorest neighbourhood and the epicentre for injection drug use (IDU), has a high rate not only of illicit drug use but also illicit drug possession and trafficking. It is estimated that nearly half of Vancouver's IDUs ( 4, 700 ID Us and 1,000 street youth) reside in this area covering approximately ten city blocks. On a day-to-to day basis, police officers routinely interact with individuals that are under the influence of illicit drugs placing themselves at risk not only of potential violent confrontation but also of inadvertently exposing themselves to communicable diseases.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".