Challenges and priorities for E-cigarette regulation at the local level – insights from an Ontario tobacco control community-of-practice
Bibliographic record
Abstract
Background: There has been minimal policy development in Canada to regulate when and where e-cigarettes can be used, and no policies to-date to set a minimum legal sale age to purchase e-cigarettes.Public Health professionals that are members of an Ontario-wide Community-of-Practice (CoP) working on tobacco control issues were surveyed about e-cigarette activity at their health units.Findings: The survey was completed by 19 respondents from 17 different health units (response rate of 63%; representing 47% of the province's health units).When respondents were asked to describe how 'high a priority' the issue of e-cigarettes was within their health unit, 88% (n = 15) reported it was a 'medium' or 'high'.The vast majority of members of the CoP (90%, n = 17) reported that their health unit is experiencing questions from the public about the safety or health risks of e-cigarettes (e.g.e-juice, nicotine cartridges, poisoning, second-hand vapour), as well as questions about the efficacy of e-cigarettes to support cessation (90%, n = 17).Almost three quarters of respondents (74%, n = 14) reported that their health unit has received complaints about people using e-cigarettes in enclosed workplaces, and roughly one quarter (26%, n = 5) reported their health unit has received complaints about outdoor e-cigarette use.Conclusions: Most members of the CoP report that their local health unit is engaged in the issue of electronic cigarettes.Local authorities including cities and regions have the jurisdictional authority to regulate many dimensions of electronic smoking products including the creation of e-cigarette 'vapour-free' environments, and regulating sales to youth.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".