Illicit cigarette purchasing after implementation of menthol cigarette bans in Canada: findings from the 2016–2018 ITC Four Country Smoking and Vaping Surveys
Bibliographic record
Abstract
OBJECTIVE: To examine the impact of menthol cigarette bans on use and purchasing of illicit cigarettes among menthol and non-menthol smokers in seven Canadian provinces. METHODS: Data from 1098 non-menthol smokers and 138 menthol smokers in Canada who completed the ITC Four Country Smoking and Vaping Survey in 2016 (pre-ban) and 2018 (post-ban). Brand validation analysis was conducted to (1) compare self-reported use of menthols versus actual use of menthols as regular brand, and verify self-reported purchasing of menthols among pre-ban menthol smokers at post-ban; and (2) assess pre-post ban changes in purchasing of illicit cigarettes from First Nations reserves among non-menthol smokers and menthol smokers. RESULTS: Among the subset of 138 pre-ban menthol smokers, 36 (19.5%) reported smoking menthols at post-ban. Brand validation analyses showed that 19 (9.0%) were actually using a non-menthol brand; of the 17 (10.5%) who were actually using a menthol brand, 13 (7.9%) bought a menthol brand at last purchase, and 4 (2.6%) bought a non-menthol brand. Among the full sample of smokers who purchased cigarettes from First Nations reserves at both pre-ban and post-ban, there was no change in purchasing of menthols (n=9 menthol smokers; 51.2% vs 51.2%, p=1.00), non-menthols (n=1024 non-menthol smokers; 9.1% vs 8.7%, p=0.69) or all cigarettes (menthol+non-menthol) (n=1086 smokers; 9.7% vs 9.2%, p=0.56). CONCLUSIONS: Actual rates of brand-verified menthol smoking were substantially lower than self-reported rates at post-ban. After Canada's menthol ban, there was no increase in illicit purchasing of menthol or non-menthol cigarettes from First Nations reserves.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".