Ethical Concerns in Tobacco Control Nonsmoker and “Nonnicotine” Hiring Policies: The Implications of Employment Restrictions for Tobacco Control
Bibliographic record
Abstract
Smoking has been restricted in workplaces for some time. A number of organizations with health promotion or tobacco control goals have taken the further step of implementing employment restrictions. These restrictions apply to smokers and, in some cases, to anyone testing positive on cotinine tests, which also capture users of nicotine-replacement therapy and those exposed to secondhand smoke. Such policies are defended as closely related to broader antismoking goals: first, only nonsmokers can be role models and advocates for tobacco control; second, nonsmoker and "nonnicotine" hiring policies help denormalize tobacco use, thus advancing a central aspect of tobacco control. However, these arguments are problematic: not only can hiring restrictions come into conflict with broader antismoking goals, but they also raise significant problems of their own.
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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 | 0.153 | 0.175 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.047 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.042 | 0.037 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".