Whose voice counts? Achieving better outcomes in global sexual and reproductive health and rights research
Bibliographic record
Abstract
⇒ Many indicators related to sexual and reproductive health and rights have worsened, with COVID-19, war and powerful conservative political movements around the world reversing decades of improvements.⇒ Improving sexual and reproductive health and rights generates a cascade effect that contributes to gender equality and power and improves overall health and well-being.⇒ Any solutions to address the problems in global sexual and reproductive health and rights research first require recognition of a fundamental disconnect between who is leading the research and the actual needs of the users of care.⇒ We encourage pursuit of transdisciplinary solutionfocused questions and research designs that address the needs of local communities by drawing on the knowledge of diverse interprofessional groups, across geographic regions, who have access to the resources and space that amplify their voices and ways of working.
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 | 0.341 | 0.356 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.033 | 0.045 |
| Open science | 0.003 | 0.035 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".