- 1-The Impact of Workplace Smoking Regulations on the Smoking Behavior of Canadian Workers
Bibliographic record
Abstract
This paper examines the impact of workplace smoking regulations on the probability that a worker is a current smoker, on the amount working smokers smoke, and examines the relationship between workplace regulations, exposure to second-hand smoke outside the home and at work, and smoking behaviour. Telephone survey data from 40,267 Canadian workers aged 20 or above interviewed in 2003-06 as part of the Canadian Tobacco Use Monitoring Survey is used to conduct the analysis. Smoking regulations are classified as fully restricted, restricted to designated areas, allowed in certain areas, and no restrictions, and are used as exogenous determinants of whether individuals smokes, of exposure to second-hand smoke at work and more generally outside the home, and of how much smokers smoke. Smoking, quantity smoked, and the joint probabilities of smoking and quantity smoked, of smoking and exposure at work or outside the home, and of quantity smoked and exposure at work or outside the home, are estimated using a variety of econometric specifications, including probit, logit, multiple regression, poisson and negative binomial regression, bivariate and instrumental variables probits, simultaneous equation, and hurdle models. All models indicate that workplace smoking regulations have substantial impacts on the probability of smoking, quantity smoked, and exposure. Simultaneous models indicate that smoking affects general exposure to secondhand smoke outside the home, but not exposure at work, that when workplace smoking policies are controlled for, general exposure adds no explanatory value to models that estimate smoking. However, workplace policies effects may be working through an effect on exposure.
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.
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 | 0.001 | 0.002 |
| 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) | 0.004 | 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".