A Systematic Review to Assess Gender Diversity in Authorship Within the Orthopaedic Surgery Literature
Bibliographic record
Abstract
Abstract Background Gender diversity trends in orthopaedic research are dynamic. While an increase of women in orthopaedics has been observed, gender imbalances continue to exist, especially in academic leadership and research roles. The purpose of our study was to assess the representation of women in authorship roles over a 20-year period. Methods We conducted a systematic review of clinical research studies published in The Journal of Bone and Joint Surgery and The Bone and Joint Journal between 1996–2000 and 2016–2020. First, corresponding and last author gender was determined using a combination of automated name analysis and manual searches. We performed chi-squared tests to assess differences in the proportion of women in each authorship position across time periods, journals, and orthopaedic subspecialties. Results Women represented 12.4% of first authors, 8.1% of last authors and 10.5% of corresponding authors. The proportion of women in first and corresponding author positions increased over time ( p < 0.001 and p < 0.001 respectively) while there was no difference for last author position ( p = 0.572). No differences were found when comparing last authors across the subspecialties ( p = 0.149 respectively); however, there was a difference for first and corresponding authors ( p = 0.019 and p = 0.024 respectively), with the highest proportion of women reported in general orthopaedics (19.0% and 17.7% respectively) and lowest in sports medicine (8.1%) and lower extremity (6.6%). Conclusion This study found improvements in the representation of women in first and corresponding author roles, however significant gaps remain, particularly in leadership positions represented by last author position. Continued monitoring and intervention are essential to promote long-term, meaningful change in the field.
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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 | 0.034 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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; both teacher heads 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".