Sex- and gender-sensitive public health research: an analysis of research proposals in a research institute in the Netherlands
Bibliographic record
Abstract
Taking sex and gender into account in public health research is essential to optimize methodological procedures, bridge the gender gap in public health knowledge, and advance gender equality. The aim of this study was to evaluate the current status of sex and gender considerations in public health research proposals in a Dutch research institute. We screened a random sample of 38 proposals submitted for review to the institute's science committee between 2011 and 2016. Using the Canadian Institutes of Health Research' Gender and Health Institute criteria for gender-sensitive research and qualitative content analysis, we assessed if, and how sex and gender were considered throughout the proposals (background, research aim, design, data collection, and analysis). Our results show that in general, both sex and gender were poorly considered. Gender was insufficiently taken into account throughout most proposals. When sex was mentioned in a proposal, its consideration was often inconsistent and fragmented. Finally, we identified common methodological pitfalls. We recommend that public health curricula and funding bodies increase their focus on implementing sex and gender in public health research, for instance through quality criteria, training programs for researchers and reviewers, and capacity building initiatives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.091 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".