Beliefs about cannabis at the time of legalization in Canada: results from a general population survey
Bibliographic record
Abstract
AIMS: Cannabis became a legally available drug in Canada in October of 2018. The objective of this study was to examine beliefs about cannabis use at the time of legalization among past year cannabis users, those who had used cannabis but not in the last year, and people who had never used cannabis. DESIGN AND METHODS: A survey of 813 participants, 18 years and over, and identified using random digit dialing methods, was made of the Canadian general population. Among other items, participants were asked a series of questions about their beliefs regarding cannabis use and recovery. RESULTS: Compared to never and ever users, participants who used cannabis in the last year regarded cannabis as less of a societal problem (mean [SD] past year use = 3.8 [2.4] versus 6.4 [2.6] and 6.0 [2.4] respectively, p = .001), than people were less likely to become addicted to cannabis if they tried it (past year use = 13.3% versus 48.3% and 25.1%, p = .001), and a larger proportion believed that recovery from cannabis without treatment was likely (past year use = 40.8% versus 14.2% and 19.3%, p = .001). All groups were equally positive of the chances of recovering from cannabis addiction with treatment (p = .72). DISCUSSION AND CONCLUSION: Beliefs about cannabis use vary substantially between those who have used the drug in the past year and those who have not. Replication of the survey at a later date is merited in order to assess the ways in which beliefs about cannabis evolve after an extended period of cannabis being available as a legal drug.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".