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Record W2754235975 · doi:10.1590/0102-311x00140315

A percepção do cumprimento das leis antifumo em bares e restaurantes em três cidades brasileiras: dados do ITC-Brasil

2017· article· pt· W2754235975 on OpenAlexaff
Felipe Lacerda Mendes, André Salem Szklo, Cristina Pérez, Tânia Maria Cavalcante, Geoffrey T. Fong

Bibliographic record

VenueCadernos de Saúde Pública · 2017
Typearticle
Languagept
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Waterloo
FundersNational Cancer InstituteWorld Health Organization
KeywordsHumanitiesPolitical scienceGeographyPhilosophy

Abstract

fetched live from OpenAlex

Passive smoking causes severe and lethal effects on health. Since 1996 Brazil has been moving forward in the implementation of anti-smoking legislation in enclosed public spaces. This article aims to evaluate the perceived enforcement of anti-smoking legislation in the cities of Porto Alegre (Rio Grande do Sul State), Rio de Janeiro and São Paulo, Brazil, based on the results of the ITC-Brazil Survey (International Tobacco Control Policy Evaluation Project). The results of the survey showed a significant reduction in the proportion of people who saw individuals smoking in restaurants and bars between 2009 and 2013 in the three cities surveyed. Concurrently there was an increase in the proportion of smokers who mentioned having smoked in the outer areas of these facilities. These results likely reflect a successful implementation of anti-smoking laws. Of note is the fact that by decreasing passive smoking we further enhance smoking denormalization among the general population, decreasing smoking initiation and increasing its cessation.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.362
Teacher spread0.312 · 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.

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

Citations4
Published2017
Admission routes1
Has abstractyes

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