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
Education and science are foundational to international development, yet gender inequities in Science, Technology, Engineering, and Mathematics (STEM) persist globally. While these disparities are widespread, most research and discourse on gender in STEM originates from the Global North. This edited collection amplifies contributions from the Global South, presenting twelve case studies supported by Canada’s International Development Research Centre (IDRC). The case studies are led by researchers across Africa and Latin America who investigate gender inequities in STEM within their local or regional contexts. Organised around four interwoven themes, (1) building gender-responsive and equitable STEM institutions, (2) leveraging data to address gender disparities, (3) fostering leadership and mentorship for women in STEM, and (4) ensuring support across academic and career pathways, the book offers a comprehensive view of the challenges and innovations shaping gender equity in STEM. Taken together, these chapters provide critical insights and recommendations to promote gender equity in STEM across the Global South and beyond.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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