On the shoulders of giants: correlation of rates of female first authorship with senior authorship gender
Bibliographic record
Abstract
Dear Editor Surgical subspecialties have historically had among the greatest gender imbalances in medicine1, manifesting in lower and slower rates of promotion among female physicians2. Publications contribute significantly to academic promotion2, but women are under-represented among authors of RCTs in surgery3. Given the importance of mentorship and sponsorship in surgical career development and promotion2, the predictors of female first authorship among RCTs of novel minimally invasive surgical (MIS) techniques were investigated, with a particular focus on the correlation between female senior (last) and female first authorship. A systematic review of RCTs examining novel MIS techniques was performed using Embase (OvidSP), MEDLINE (OvidSP), and Cochrane (Wiley) databases. The search strategy has been published previously3. Study selection was performed independently by three reviewers. Data were independently abstracted by two researchers and verified by two separate researchers. This review was conducted in concordance with PRISMA guidelines and was registered prospectively in the PROSPERO database (CRD4202021158). For each study, first and last author names were extracted. Author gender was determined via an online search using full name, institutional affiliation, and year of publication, and subsequently validated using Genderize.io (https://genderize.io/). Study variables included: last author gender, study design, sample size, median follow-up, participant age and gender, risk of bias, number of participating centres/nations, and funding source. χ2 and Fisher’s exact tests were used for univariable comparisons. Univariable and multivariable logistic regression analyses were used to calculate predictors of female first authorship. Only variables significant in univariable analyses were included in the multivariable model. Variable multicollinearity was evaluated using the variance inflation factor test; a cut-off value of 5 excluded variables on the basis of high degree of multicollinearity. The likelihood ratio test was used to determine the overall significance of categorical variables. P < 0.050 was considered statistically significant. All statistical analyses were undertaken using R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria). Among 9321 initial citations, 496 were deemed eligible, although it was not possible to determine first or last author gender in nine studies. Women were first author in 66 (13.9%) and last author in 60 (12.1%) studies. Of studies with female last authors, 13 (21%) also had a female first author, whereas 53 studies (12.8%) with a male last author had a female first author (Table 1). In both univariable (OR 1.93, 95 per cent c.i. 0.94 to 3.73) and multivariable (adjusted OR 1.71, 0.80 to 3.46) logistic regression models, female senior authorship was not associated with increased odds of female first authorship. RCTs with female-only patient populations were more likely to have a female first author (OR 2.46, 1.08 to 5.30; P = 0.025). First and last author gender in RCTs of minimally invasive surgical techniques Values in parentheses are percentages. Among RCTs in surgery, there was no significant correlation between female senior authors and female first authors; however, there was a non-significant trend towards trials with female senior authors being more likely to have female first authors. This non-significant trend suggests that female senior surgeon mentorship may be influential in academic success for early-career female surgeons. Although it included RCTs published over more than 30 years, the present analysis was underpowered to demonstrate a statistically significant relationship between last author gender and the likelihood of female first authorship. Inclusion of as few as 50 more studies would have provided more than 50 per cent probability of conventional statistical significance (P < 0.050)4. Gender diversity has been shown to improve team and work quality across a variety of industries. As women are penalized for diversity-valuing behaviours5, it is paramount that men embrace the role of mentoring women in surgery. Female authors also demonstrate increased focus on female-only populations, illustrating a heightened awareness of issues affecting women. A.N.L. and C.J.D.W. are joint senior authors of this article. Disclosure. The authors declare no conflict of interest.
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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 | 0.006 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".