Does a Change in Health Research Funding Policy Related to the Integration of Sex and Gender Have an Impact?
Bibliographic record
Abstract
We analyzed the impact of a requirement introduced in December 2010 that all applicants to the Canadian Institutes of Health Research indicate whether their research designs accounted for sex or gender. We aimed to inform research policy by understanding the extent to which applicants across health research disciplines accounted for sex and gender. We conducted a descriptive statistical analysis to identify trends in application data from three research funding competitions (December 2010, June 2011, and December 2011) (N = 1459). We also conducted a qualitative thematic analysis of applicants' responses. Here we show that the proportion of applicants responding affirmatively to the questions on sex and gender increased over time (48% in December 2011, compared to 26% in December 2010). Biomedical researchers were least likely to report accounting for sex and gender. Analysis by discipline-specific peer review panel showed variation in the likelihood that a given panel will fund grants with a stated focus on sex or gender. These findings suggest that mandatory questions are one way of encouraging the uptake of sex and gender in health research, yet there remain persistent disparities across disciplines. These disparities represent opportunities for policy intervention by health research funders.
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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 | 0.121 | 0.226 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".