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Record W3090580783 · doi:10.24095/hpcdp.29.2.07

Cross Canada Forum: The national lung health framework: an opportunity for gender analysis

2009· article· en· W3090580783 on OpenAlexafffundvenueabout
Natalie Hemsing, Lorraine Greaves

Bibliographic record

VenueChronic diseases in Canada · 2009
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsBritish Columbia Centre of Excellence for Women's Health
FundersHealth CanadaProvincial Health Services Authority
KeywordsMedicineSmoking cessationEnvironmental healthDiseaseGerontologyPathology

Abstract

fetched live from OpenAlex

Smoking related respiratory diseases in Canada represent a huge social and economic burden for both women and men. This article addresses the potential impact of the National Lung Health Framework for reducing disparities between women and men in respiratory health and between sub-populations of women and men. A preliminary analysis of the existing framework documents indicates that sex and gender factors, differences and influences have not yet been clearly or sufficiently identified. Yet, there are sex and gender issues related to tobacco prevention and cessation, lung health and lung disease. In particular, we consider the specific respiratory health needs and experiences of women to demonstrate the need for sex and gender-based analysis within the framework. For example, while there is inconsistent evidence regarding quit rates, women and men have different cessation patterns and reasons for smoking. Although creating a Canada-specific approach to lung health is an important initiative, the sex and gender issues associated with respiratory disease and health need to be explicitly addressed in the planning and development stages of the framework in order to have a beneficial and lasting impact on both women and men.

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)0.000
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 score0.045
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.049
GPT teacher head0.380
Teacher spread0.330 · 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

Citations0
Published2009
Admission routes4
Has abstractyes

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