Prescribe with caution: the response of Canada's medical regulatory authorities to the therapeutic use of cannabis
Bibliographic record
Abstract
Canada was one of the first countries worldwide to legalize the use of cannabis for therapeutic purposes. The federally regulated cannabis access program has not had the support of medical regulatory authorities, however, and recent changes to federal rules are controversial in imposing responsibility on physicians to prescribe the drug, which is unapproved and illegal outside the medical use laws. This paper analyzes the response of Canada’s ten medical regulatory authorities to these legal changes and provides critical commentary on the legal and ethical guidance provided to physicians who treat patients seeking to use cannabis therapeutically. The paper considers the role of doctors as gatekeepers, the profession’s concerns about medico-legal risks of cannabis prescription, stigmatization and barriers to care for patients who use cannabis, and the need for research to continue to build the evidence base to inform therapeutic prescription of the drug. The Canadian experience provides lessons for other jurisdictions that are considering liberalizing cannabis use laws.
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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 | 0.016 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.052 | 0.044 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.012 | 0.023 |
| 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 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".