Authorship diversity in general surgery-related Cochrane systematic reviews: a bibliometric study
Bibliographic record
Abstract
Despite efforts to address fundamental inequities, surgical residencies lag behind their non-surgical counterparts in attracting women 1 .Equity of representation in authorship is an important aspect of evidence-based medicine.This study analysed representation in authorship of general surgery-related Cochrane systematic reviews with respect to gender and country.Data were collected from the Cochrane Library on 3 September 2022, using the keyword 'general surgery' in an advanced search under the subheading 'All Text'.An online search was used to confirm the gender and country of an author, by discovering a minimum of two web pages (such as LinkedIn, institutional websites, Loop profile, junior editorial profile, and ResearchGate) demonstrating them.The corresponding authors were contacted when deemed necessary.Some 250 publications that included 1420 authors were included.Four authors had affiliations to two countries.The leading five nations represented in authorship were the UK (562, 39.4 per cent), China (163, 11.5 per cent), Italy (144, 10.1 per cent), Canada (91, 6.4 per cent), and the USA (89, 6.2 per cent) (Fig. 1a).Syria was the only low-income country that had representation and constituted 0.3 per cent (5 authors).India (8, 0.6 per cent) and Nigeria (2, 0.1 per cent) were the only countries from lowermiddle-income groups that had representation.The male to female ratio in this study was 2.11 : 1 (957 : 453) (Fig. 1b).Gender data for 10 authors could not be retrieved and these were categorized as 'unknown'.There were 169 male (67.3 per cent) and 82 female (32.6 per cent) first authors (gender ratio 2.06 : 1).One study had designated two authors as co-first authors.Eighty-one women constituted 32.4 per cent of all the corresponding authors (male to female gender ratio 2.06 : 1).One article had no corresponding author.One hundred and fifty studies (60 per cent) did not have a female in a lead author (first or corresponding author) position.Fifty-eight studies (23.2 per cent) did not have any female authors, whereas only eight (3.2 per cent) did not have any male authors.In low-income countries, 1 in 5 authors were female.Similarly, in low-middle-income countries, 2 of 10 authors were female.There were no lead female authors
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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 | 0.051 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.016 | 0.049 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 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".