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Record W156222421

Smoking bans: influence on smoking prevalence.

2007· article· en· W156222421 on OpenAlexaffabout
Margot Shields

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsTranstheoretical modelSmoking prevalenceSmoking cessationContext (archaeology)MedicineEnvironmental healthCurrent Population SurveyPopulationDemographyTobacco controlLongitudinal dataPublic healthPsychological interventionPsychiatryGeographyNursing
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: This article reports trends in smoking prevalence and smoking restrictions in Canada since 2000, and examines associations between home and workplace restrictions and smoking cessation. DATA SOURCES: Data are from the Canadian Tobacco Use Monitoring Survey and the longitudinal component of the National Population Health Survey. ANALYTICAL TECHNIQUES: Trends in smoking prevalence and smoking restrictions were calculated. Associations between home and workplace smoking restrictions and smoking cessation were examined in the context of the Transtheoretical Model, which proposes that smokers go through five distinct stages in attempting to quit. The likelihood of current and former smokers being at specific stages was studied in relation to smoking restrictions at home and at work. Longitudinal data were used to determine if home and workplace smoking restrictions were predictors of quitting over a two-year period. MAIN RESULTS: Since 2000, Canadians smokers have faced a growing number of restrictions on where they can smoke. Bans at home and at work were associated with a reduced likelihood of being in the initial "stages of change," and an increased likelihood of being in the latter stages. Smokers who reported newly smoke-free homes or workplaces were more likely to quit over the next two years, compared with those who did not encounter such restrictions at home or at work.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.284
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations72
Published2007
Admission routes2
Has abstractyes

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