The effect of legislation concerning environmental tobacco smoke (ETS) on the short-term health of hospitality workers: A Canada â Italy comparison
Bibliographic record
Abstract
Background: Environmental tobacco smoke (ETS) is a combination of the smoke exhaled by smokers and the smoke burning from a cigarette, cigar or pipe that is not being inhaled. It contains over 4000 chemicals many of them being known carcinogens and toxins. The recently-identified hazards of ETS have resulted in the implementation of new legislation to protect non-smokers’ health in jurisdictions worldwide. Purpose: This study tests the hypothesis that legislation eliminating ETS from all enclosed public places improves the health of hospitality workers. Methods: This is a descriptive, case-series study, which investigates tobacco smoke exposure in non-smoking hospitality workers in Canada and Italy. Data was obtained by testing workers for levels of carbon monoxide before and immediately after working in venues where smoking was permitted and was not permitted. Workers also provided information on respiratory and sensory irritation symptoms. Conclusion: Legislation eliminating ETS improves the health of hospitality industry workers.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".