Smokers’ support for tobacco endgame measures in Canada: findings from the 2016 International Tobacco Control Smoking and Vaping Survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The Canadian government has committed to an endgame target of less than 5% tobacco use by 2035. The aims of this study were to assess baseline levels of support for potential endgame policies among Canadian smokers, by province/region, demographic characteristics and smoking-related correlates, and to identify predictors of support. METHODS: We analyzed data for 3215 adult (age ≥ 18 yr) smokers from the Canadian arm of the 2016 International Tobacco Control Four Country Smoking and Vaping Survey. We estimated weighted percentages of support for endgame measures for 6 provinces/regions of the country. We used weighted logistic regression models to identify predictors of support for 14 endgame strategies. RESULTS: Among cigarette endgame policies, support was highest for reducing nicotine content (70.2%), raising the legal age for purchase (69.8%), increasing access to alternative nicotine products (65.8%) and banning marketing (58.5%). Among e-cigarette policies, there was majority support for restricting youth access (86.1%), restricting nicotine content (64.9%), prohibiting use in smoke-free places (63.4%) and banning marketing (54.8%). The level of support for other endgame measures ranged from 28.9% to 45.2%. Support for cigarette and e-cigarette policies was generally higher among smokers with intentions to quit and those from Quebec. Support for e-cigarette policies was generally lower among smokers who also used e-cigarettes daily. INTERPRETATION: There is considerable support among Canadian smokers for endgame policies that go beyond current approaches to tobacco control. Our findings provide a baseline for evaluating future trends in smokers' support for innovative measures to radically reduce smoking rates in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it