Comprehensive tobacco control policies and the smoking behaviour of Canadian adults
Bibliographic record
Abstract
OBJECTIVE: To examine the associations of cigarette prices, restrictions on public smoking, and health education with the odds of adult smoking and amount smoked daily. DESIGN: Multi-level analysis of adult (age 25+) smoking patterns in Canada's National Population Health Survey, after adding administrative data on prices, bylaws, and health education according to the survey respondent's place of residence. SETTING/SUBJECTS: Population based sample of Canadians age 25+ in households (n = 14 355). OUTCOME MEASURES: Smoking status, amount consumed daily. ANALYSIS: Logistic regression for smoking status, multiple regression for amount smoked, with controls for age, education, marital status; separate analyses for men and women. RESULTS: Cigarette prices were positively associated with the odds of being a non-smoker and negatively with amount smoked, for adults of both sexes. Per capita health education expenditures were positively associated with the odds of being a non-smoker and negatively with amount smoked--for men but not women. The restrictiveness of municipal bylaws limiting public smoking was positively associated with the odds of being a non-smoker and negatively with amount smoked--for women but not men. These results are independent of age, education, and marital status. CONCLUSIONS: To be effective, tobacco control must comprise a mix of strategies as men and women respond differently to health education and restrictions on public smoking; taxation, reflected in higher cigarette prices, is the only one of these measures related to smoking for both sexes. This model permits calculations of the level of increase in each measure that is required to reduce the prevalence of smoking by a specified amount.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".