MétaCan
Menu
Back to cohort
Record W4375857256 · doi:10.1093/bjs/znad117

Authorship diversity in general surgery-related Cochrane systematic reviews: a bibliometric study

2023· article· en· W4375857256 on OpenAlexaboutno aff
Roger B Rathna, Jyotirmoy Biswas, Christopher D’Souza, Jethin Mathew Joseph, Vincent Kipkorir, Arkadeep Dhali

Bibliographic record

VenueBritish journal of surgery · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSystematic reviewBibliometricsDiversity (politics)MEDLINELibrary scienceAnthropology

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.051
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0510.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0160.049
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.208
GPT teacher head0.362
Teacher spread0.154 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBritish journal of surgerySame topicDiversity and Career in MedicineFrench-language works237,207