Discourse / Discours : Research Priorities in Gender and Health
Bibliographic record
Abstract
This year we witnessed an unprecedented event, the creation and exponential growth of a national research institute devoted to the study of gender and health. The launch of the Canadian Institutes of Health Research (CIHR) Institute of Gender and Health represented the culmination of directions recommended by research- and policy-influencing groups in Canada. Key international and national initiatives that provided a foundation for this Institute were the Canada-USA Women's Health Forum in 1996; the development of five Centres of Excellence on Women's Health, funded by Health Canada in 1996; and the creation of Wyeth-Ayerst and MRC-PMAC Clinical Research Chairs in Women's Health. Guiding documents included CIHR 2000: Sex, Gender and Women's Health (British Columbia Centre of Excellence for Women's Health, 1999), A Women's Health Research Institute in the Canadian Institutes of Health Research (Working Group on CIHR, Gender and Women's Health Research, 2000), and Agenda for Research on Women's Health for the 21st Century (National Institutes of Health, 1999).
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 | 0.094 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.030 | 0.101 |
| Scholarly communication | 0.033 | 0.035 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.016 | 0.026 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".