International differences in patterns of cannabis use among adult cigarette smokers: Findings from the 2018 ITC Four Country Smoking and Vaping Survey
Bibliographic record
Abstract
BACKGROUND: Although evidence shows that co-use of cigarettes and cannabis is common, there is little research examining if co-use patterns vary depending on the regulatory environment for cannabis. This study examined patterns of co-use and perceptions of relative harm among cigarette smokers in four countries with different histories, and at different stages of cannabis legalization. METHODS: Data are from the 2018 International Tobacco Control 4CV Survey and included 10035 adult cigarette smokers from Canada, United States (US), Australia, and England. At the time of the survey, Canada and the US had relatively more permissive cannabis regulations compared to Australia and England. RESULTS: Among this sample of 10035 cigarette smokers, Canada had the highest rate of cannabis co-use in the last 12 months (36.3%), followed by the US (29.1%), England (21.6%), and Australia (21.4%). Among past 12 month co-users (n = 3134), the US (40.2%) and Canada (35.2%) had the highest rates of daily cannabis use, followed by smokers in England (26.3%) and Australia (21.7%); Australian co-users had the highest rate of infrequent (
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".