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Record W2162729523 · doi:10.3390/ijerph120201449

The Meanings of Smoking to Women and Their Implications for Cessation

2015· article· en· W2162729523 on OpenAlexaff
Lorraine Greaves

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2015
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsBritish Columbia Centre of Excellence for Women's Health
Fundersnot available
KeywordsSmoking cessationContext (archaeology)Psychological interventionMotivational interviewingPublic healthHealth promotionHarmAffect (linguistics)Harm reductionPromotion (chess)MedicinePsychologySocial psychologyPsychiatryPolitical scienceNursingPolitics

Abstract

fetched live from OpenAlex

Smoking cigarettes is a gendered activity with sex- and gender-specific uptake trends and cessation patterns. While global male smoking rates have peaked, female rates are set to escalate in the 21st century, especially in low and middle income countries. Hence, smoking cessation for women will be an ongoing issue and requires refreshed attention. Public health and health promotion messages are being challenged to be increasingly tailored, taking gender into account. Women-centred approaches that include harm-reduction, motivational interviewing and trauma-informed elements are the new frontiers in interventions to encourage smoking cessation for women. Such approaches are linked to the meanings of smoking to women, the adaptive function of, and the overall role of smoking cigarettes in the context of women's lives. These approaches respect gender and sex-related factors that affect smoking and smoking cessation and respond to these issues, not by reinforcing destructive or negative gender norms, but with insight. This article discusses a women-centred approach to smoking cessation that could underpin initiatives in clinical, community or public health settings and could inform campaigns and messaging.

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)0.003
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 score0.485
Threshold uncertainty score0.115

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.157
GPT teacher head0.432
Teacher spread0.275 · 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

Citations97
Published2015
Admission routes1
Has abstractyes

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