Would the Public Support a Ban on Smoking in Public Places? - A Survey of Local Opinion in the North East of England
Bibliographic record
Abstract
The purpose of study is to determine the degree of support for a general ban on smoking in public places and bans on smoking in specific locations amongst adults living in the North East of England. To assess the variation in support for smoking bans by smoking status and socio-demographic factors. Procedures: After appropriate training, ten medical students conducted interviews with members of the public in city centre locations. Interviewers adhered to a structured schedule and all participants gave informed consent. Quota sampling techniques were used to obtain a sample representative of the wider population in terms of age, gender and occupational social class. Main findings: Interviews were conducted with 538 individuals of whom 338 (63%) stated that they would support a general ban on smoking in public places. Support for a ban varied by smoking status and social class but not by gender or age group. Of the specific locations mentioned, support was greatest for smoking bans in restaurants and cafes (83%), shopping malls (72%) and workplaces (72%) and lowest for smoking bans in pubs and clubs (37%), the home (27%) and outdoor public places (23%). Conclusions: Local support for bans on smoking in public places in the North East of England is high - particularly in relation to bans in restaurants and cafes, shopping malls and workplaces. Introduction and enforcement of smoking bans in these locations would not be expected to meet with great opposition and may have a positive influence on public health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".