Reshuffling and Relocating: The Gendered and Income-Related Differential Effects of Restricting Smoking Locations
Bibliographic record
Abstract
This study investigates secondhand smoke (SHS) exposure and management in the context of smoking location restrictions, for nonsmokers, former, and current smokers. A purposive sample of 47 low income and non-low-income men and women of varied smoking statuses was recruited to participate in a telephone interview or a focus group. Amidst general approval of increased restrictions there were gendered patterns of SHS exposure and management, and effects of SHS policies that reflect power, control, and social roles that need to be considered as policies are developed, implemented and monitored. The experience of smoking restrictions and the management of SHS is influenced by the social context (relationship with a partner, family member, or stranger), the space of exposure (public or private, worksite), the social location of individuals involved (gender, income), and differential tolerance to SHS. This confluence of factors creates differing unintended and unexpected consequences to the social and physical situations of male and female smokers, nonsmokers, and former smokers. These factors deserve further study, in the interests of informing the development of future interventions and policies restricting SHS.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".