On the relationship between gender disparities in scholarly communication and country-level development indicators
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Gender disparities in science remain, despite decades of policies aimed at achieving gender parity. Yet, little is known about the macro-level factors affecting such disparities. This paper examines the degree to which country-level human development indicators (HDI) and gender inequality indicators (GII) gathered by the United Nations Development Report can reveal systemic gender inequalities in scholarship. Countries ‘low’ in HDI and GII had the lowest contribution of female participation in science and highest degree of international collaboration. Research from highly developed countries was more cited, although gender disparities remained. For HDI, gross national income was a strong predictor of scientific output and impact (and, to a lesser degree, collaboration). The rate of women in the labor force was the strongest predictive variable in GII, explaining differences in output, collaboration, and impact. However, predictive variables differed by HDI/GII quartile, suggesting that monolithic policies may not be appropriate for addressing gender disparities in science.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it