Support for removal of point-of-purchase tobacco advertising and displays: findings from the International Tobacco Control (ITC) Canada survey
Bibliographic record
Abstract
BACKGROUND: Although most countries now have at least some restrictions on tobacco marketing, the tobacco industry meet these restrictions by re-allocating expenditure to unregulated channels, such as at point-of-purchase. METHODS: Longitudinal data from 10 Canadian provinces in the International Tobacco Control Survey was analysed to examine adult smokers' support for a ban on tobacco advertising and displays in stores and whether this support is associated with noticing either advertising or displays in stores, and quit intentions, over time. In total, there were 4580 respondents in wave 5 (October 2006 to February 2007), wave 6 (September 2007 to February 2008) and wave 7 (October 2008 to June 2009). The surveys were conducted before, during and in some cases after the implementation of display bans in most Canadian provinces and territories. RESULTS: Smokers in all provinces showed strong support for a ban on tobacco displays over the study period. Levels of support for an advertising and display ban were comparable between Canadian provinces over time, irrespective of whether they had been banned or not. Noticing tobacco displays and signs in-store was demonstrably less likely to predict support for display (OR=0.73, p=0.005) and advertising (OR=0.78, p=0.02) ban, respectively. Smokers intending to quit were more likely to support advertising and display bans over time. CONCLUSION: This study serves as a timely reminder that the implementation of tobacco control measures, such as the removal of tobacco displays, appear to sustain support among smokers, those most likely to oppose such measures.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".