Cannabis use and workplace cannabis availability, perceptions and policies among Canadian workers: a comparison before and after the legalisation of non-medical cannabis
Bibliographic record
Abstract
OBJECTIVES: Little data exist examining the impact of non-medical (recreational) cannabis legalisation among a working population. The objective was to compare cannabis use patterns and workplace risk perceptions, cannabis availability and workplace use policies before and almost 1 year after legalisation in Canadian workers. METHODS: Two overlapping cross-sectional samples of Canadian workers were surveyed 4 months before legalisation (time 1 (T1), n=2011) and 9-11 months after legalisation (time 2 (T2), n=4032), gathering information on cannabis use (overall and workplace use), workers' perceptions regarding risks of workplace use, availability of cannabis at work and awareness of workplace substance use policies. The marginal distributions of these variables at T1 and T2 were compared, adjusting for sociodemographic, work and health and lifestyle factors. RESULTS: Cannabis use status changed from prelegalisation to postlegalisation (p<0.0001), with fewer respondents reporting former use (ie, more than 1 year ago; 40.4% at T1, 33.0% at T2) and a greater proportion of workers reporting past-year use (30.4% at T1, 39.3% at T2). Never use remained stable (29.2% at T1, 27.6% at T2). Workplace cannabis use also remained stable (9.4% at T1, 9.1% at T2; p=0.4580). At T1, 62.7% of respondents reported being aware of their workplace having a substance use policy, increasing to 79.0% at T2 (p<0.0001). Small magnitude changes occurred in perceptions of risk and workplace availability. CONCLUSIONS: Results point to a lack of substantive changes in the short-term from prelegalisation to postlegalisation. Longer-term data among workers are needed given the evolving nature of this legislative policy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".