Implications of Cannabis Legalization on Substance-Related Benefits and Harms for People Who Use Opioids : A Canadian Perspective
Bibliographic record
Abstract
In 2018, Canada enacted the Cannabis Act, becoming only the second country (after Uruguay) to legalize the recreational consumption of cannabis. Although there is ongoing global disagreement on the risk-benefit profile of cannabis with increasing legalization in many parts of the world, the evidence of rising cannabis use prevalence post-legalization has been consistent. In contrast, post-legalization changes in various cannabis-related metrics have been inconsistent in Canada and other parts of the world. Furthermore, the implications of cannabis legalization on substance-related harms and benefits for people who use unregulated drugs (PWUD), particularly opioids, remain unclear. Finally, while Canada did not legalize cannabis to address the opioid crisis, there is rising scientific and popular interest in the therapeutic potential of cannabis to mitigate opioid-related harms. This perspective highlights the implications of cannabis legalization on substance-related benefits and harms for people who use opioids, the current state of Canadian research, and suggestions for future directions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".