Safer supply and political interference in medical practice: Alberta's Narcotics Transition Services
Bibliographic record
Abstract
Across much of Canada, opioid poisoning deaths have been increasing due to a toxic, contaminated, and unpredictable drug supply. Multiple prescribed safer supply pilot projects are being implemented and evaluated in an attempt to save lives. In the province of Alberta, however, new regulations introduced in 2022 significantly constrain safer supply prescribing by banning the prescription, dispensing, and administration of safer supply outside of a very limited number of clinics. In this commentary, we review prescribed safer supply programs in Canada and outline how the Alberta Government's change in regulations conflict with emerging evidence and efforts by other jurisdictions to address the rising opioid poisoning deaths. We examine the development of these regulations and analyze how the Alberta government shaped and justified this restrictive policy. We conclude by identifying important lessons learned from the experience in Alberta for researchers, healthcare providers, and decisionmakers in other jurisdictions.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.016 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".