Promoting gender equity through health research: impacts and insights from a Canadian initiative
Bibliographic record
Abstract
The World Health Organization (WHO) recently identified major knowledge gaps regarding gender and sex as determinants of health. Canada recognized the importance of mobilizing research, and informing programs and policies focused on promoting the health of males and females across their lifespans by creating a national research institute that is focused on the study of gender, sex and health. No other country has created a national research institute dedicated to gender and health. Other countries may benefit from the strategies used by this Canadian research institute to create and sustain success, including: (i) mechanisms for defining national research priorities; (ii) tools to optimize research excellence; (iii) vehicles to build research capacity and develop a research community; (iv) processes to convert new knowledge into practice, programs and policies; (v) creation of partnerships at both the national and international levels and (vi) solutions to challenges and obstacles. The development of a vibrant research community and powerful national and international collaborations promotes gender and health equity.
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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 | 0.044 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.023 | 0.013 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".