MétaCan
Menu
Back to cohort
Record W2044329749 · doi:10.1136/jech.2005.045393

Tobacco policies and vulnerable girls and women: toward a framework for gender sensitive policy development

2006· article· en· W2044329749 on OpenAlexafffund
Lorraine Greaves, Natasha Jategaonkar

Bibliographic record

VenueJournal of Epidemiology & Community Health · 2006
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsBritish Columbia Centre of Excellence for Women's HealthHealth Canada
FundersHealth Canada
KeywordsVulnerability (computing)DisadvantageMedicineUnintended consequencesTobacco controlAffect (linguistics)Diversity (politics)Public policyPublic healthTobacco useHealth policyEnvironmental healthInequalityPublic economicsDemographic economicsEconomic growthPolitical sciencePsychologyNursingPopulationEconomics

Abstract

fetched live from OpenAlex

This article assesses the effects of comprehensive tobacco control policies on diverse subpopulations of girls and women who are at increased vulnerability to tobacco use because of disadvantage. The authors report on a recent assessment of experimental literature examining tobacco taxation; smoking location restrictions in public and private spaces; and sales restrictions. A comprehensive search was undertaken to identify relevant studies and evaluation reports. Gender based and diversity analyses were performed to identify pertinent sex differences and gender influences that would affect the application and impact of the policy. Finally, the results were contextualised within the wider literature on women's tobacco use and women's health. The authors consider not only the intended policy effects, but also explicitly examine the gendered and/or unintended consequences of these policies on other aspects of girls and women's health and wellbeing. A framework for developing gender sensitive tobacco programmes and policies for low income girls and women is provided.

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)0.008
metaresearch head score (Gemma)0.003
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 score0.016
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.154
GPT teacher head0.438
Teacher spread0.284 · 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

Citations78
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Epidemiology & Community HealthSame topicSmoking Behavior and CessationFrench-language works237,207