A breath of fresh air: The effect of public smoking bans on Indigenous youth
Bibliographic record
Abstract
In general, past studies have estimated the average effect of public smoking bans on youth, ignoring differences across sub-populations. We extend the literature by considering Indigenous youth, who are a vulnerable and previously unexamined group (however, our analysis excludes First Nations youth who live on reserve). We also consider previously unexamined outcomes among youth: self-assessed health and subjective well-being. Our difference-in-differences estimates from Canada indicate that public bans reduced youth smoking and second-hand exposure in public places, on average. There was no displacement on the extensive margin, but the bans increased the number of people who smoke in the homes of youth, conditional on the presence of smokers in the household. Beyond average effects, however, we find that public bans reduced second-hand exposure in the homes of Indigenous youth (particularly Métis youth), on the extensive and intensive margins. The same youth experienced concurrent improvements in self-assessed health and life satisfaction. We conclude that public bans mitigate disparities in health and well-being between Indigenous and non-Indigenous youth, but the extent varies across Indigenous sub-populations, even within a particular country.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".