How have health promotion frameworks considered gender?
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.056 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.009 | 0.035 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".