Brazilian authorship gender trends on academic surgery: a bigdata analysis
Bibliographic record
Abstract
PURPOSE: To evaluate the gender distribution of first and last authors with Brazilian surgical affiliations in PubMed-indexed surgical journals. METHODS: Data from eligible surgical journals were retrieved using Scimago Journal & Country Rank 2021 and manually reviewed. Manuscripts published from 2018 to 2022 were included if at least one author was affiliated with a Brazilian institution and a surgical specialty. RESULTS: Data from 340 eligible surgical journals were included. We analyzed first and last authors' forenames of 1,881 manuscripts. Women comprised 16.7% of the first and 12.4% of the last authors. Analyzing the differences in gender trends in authorship across the five Brazilian regions, we found that the South had the highest representation, while the Midwest and North showed the lowest, respectively. Obstetrics and gynecology featured the highest percentage of women-first authors, whereas orthopedics had the lowest. For the last authorship, pediatric surgery showed the highest, with hand surgery having the lowest representation. Male first authors were 1.9 times more likely to engage in international collaborations. CONCLUSIONS: This study suggests the persistent underrepresentation of Brazilian women in surgical journal authorship. Local policy changes should be considered to encourage greater diversity and inclusivity in surgical research.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".