Flavored Tobacco Use Among Canadian Students in Grades 9 Through 12: Prevalence and Patterns From the 2010–2011 Youth Smoking Survey
Bibliographic record
Abstract
INTRODUCTION: This study examined patterns of use of flavored tobacco products in a nationally generalizable sample of Canadian students in grades 9 through 12 after the implementation of a national ban on certain flavored tobacco products. METHODS: Data from the 2010-2011 Youth Smoking Survey, a nationally generalizable sample of Canadian students in grades 9 through 12 (n = 31,396), were used to examine tobacco product use. Logistic regression models were used to examine differences in use of flavored tobacco products (cigarettes, pipes, little cigars or cigarillos, cigars, roll-your-own cigarettes, bidis, smokeless tobacco, water pipes, and blunt wraps) by sociodemographic and regional characteristics. RESULTS: Approximately 52% of young tobacco users used flavored products in the previous 30 days. Flavored tobacco use varied by product type and ranged from 32% of cigarette smokers reporting menthol smoking to 70% of smokeless tobacco users reporting using flavored product in the previous 30 days. The percentage of last-30-day users who used flavored tobacco was significantly higher in Quebec than in Ontario and significantly higher among youths who received weekly spending money than among those who received no money. CONCLUSION: More than half of tobacco users in grades 9 through 12 in Canada use flavored tobacco, despite a national ban on certain flavored tobacco products.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".