Gender equity in health research publishing in Africa
Bibliographic record
Abstract
INTRODUCTION: Women researchers find it more difficult to publish in academic journals than men, an inequity that affects women's careers and was exacerbated during the pandemic, particularly for women in low-income and middle-income countries. We measured publishing by sub-Saharan African (SSA) women in prestigious authorship positions (first or last author, or single author) during the time frame 2014-2016. We also examined policies and practices at journals publishing high rates of women scientists from sub-Saharan Africa, to identify potential structural enablers affecting these women in publishing. METHODS: The study used Namsor V.2, an application programming interface, to conduct a secondary analysis of a bibliometric database. We also analysed policies and practices of ten journals with the highest number of SSA women publishing in first authorship positions. RESULTS: Based on regional analyses, the greatest magnitude of authorship inequity is in papers from sub-Saharan Africa, where men comprised 61% of first authors, 65% of last authors and 66% of single authors. Women from South Africa and Nigeria had greater success in publishing than those from other SSA countries, though women represented at least 20% of last authors in 25 SSA countries. The journals that published the most SSA women as prominent authors are journals based in SSA. Journals with overwhelmingly male leadership are also among those publishing the highest number of SSA women. CONCLUSION: Women scholars in SSA face substantial gender inequities in publishing in prestigious authorship positions in academic journals, though there is a cadre of women research leaders across the region. Journals in SSA are important for local women scholars and the inequities SSA women researchers face are not necessarily attributable to gender discrepancy in journals' editorial leadership.
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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 | 0.023 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".