Prescribing safe supply: ethical considerations for clinicians
Bibliographic record
Abstract
The COVID-19 pandemic has exacerbated the drug poisoning epidemic in a number of ways: individuals use alone more often, there is decreased access to harm reduction services and there has been an increase in the toxicity of the unregulated drug supply. In response to the crisis, clinicians, policy makers and people who use drugs have been seeking ways to prevent the worst harms of unregulated opioid use. One prominent idea is safe supply. One form of safe supply enlists clinicians to prescribe opioids so that people have access to drugs of known composition and strength. In this paper, we assess the ethical case for clinicians providing this service. As we describe, there is much that is unknown about safe supply. However, given the seriousness of the overdose death epidemic and the current limited evidence for safe supply's efficacy, we argue that it is ethically permissible for clinicians to begin prescribing opioids for some select patients.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".