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Record W2168071629 · doi:10.1093/heapro/dar087

How have health promotion frameworks considered gender?

2011· article· en· W2168071629 on OpenAlexafffundabout
Karen Gelb, Ann Pederson, Lorraine Greaves

Bibliographic record

VenueHealth Promotion International · 2011
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsBritish Columbia Centre of Excellence for Women's Health
FundersCanadian Institutes of Health ResearchHealth Canada
KeywordsHealth promotionPromotion (chess)Health policyHealth educationMedicinePsychologyPublic relationsNursingPolitical sciencePublic health

Abstract

fetched live from OpenAlex

This paper provides an overview of five key internationally recognized health promotion frameworks and assesses their consideration of gender. This analysis was conducted as part of the Promoting Health in Women project, a Canadian initiative focused on generating a framework for effective health promotion for women. To date, no review of health promotion frameworks has specifically focused on assessing the treatment of gender. This analysis draws on a comprehensive literature review that covered available literature on gender and health promotion frameworks published internationally between 1974 and 2010. Analysis of five key health promotion frameworks revealed that although gender was at times mentioned as a determinant of health, gender was never identified and integrated as a factor critical to successful health promotion. This superficial attention to the role of gender in health promotion is problematic as it limits our capacity to understand how gender influences health, health contexts and health promotion, as well as our ability to integrate gender into future comprehensive health promotion strategies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.307
GPT teacher head0.493
Teacher spread0.186 · 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

Citations46
Published2011
Admission routes3
Has abstractyes

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