Who coauthors Cochrane Reviews related to genitourinary cancers? A 1998-2022 analysis of country and gender diversity.
Bibliographic record
Abstract
436 Background: Women and individuals from low- and lower-middle-income countries (LMICs) are under-represented in urology literature, particularly in high-impact publications. Cochrane, a non-profit collaboration, publishes high‐quality systematic reviews that frequently impact policy and clinical practice worldwide. However, the state of the country and gender diversity amongst authors of urology-related Cochrane Reviews is unknown, which this work sought to determine. Methods: We searched the Cochrane Database, under the filter “Topic: Urology”, for all reviews related to genitourinary cancers, published until 25 July 2022, including both active reviews and those withdrawn for updation. We extracted authorship data and classified the national affiliation of authors into either high- and upper-middle-income countries (HICs) or LMICs based on the World Bank income classification. We treated a collaborative author group belonging to one country as a single-country affiliation. Given the higher accuracy of manual web searches for ascertaining gender over algorithmic estimation, we utilized the former to achieve ≥90% ascertainment. We endeavored to capture at least one webpage that demonstrated their gender, e.g. institutional profile, Google Scholar, ResearchGate, etc. Results: A total of 54 urology-related reviews, co-authored by a total of 324 authors, were included. 53 reviews were published by the Cochrane Urology Group, while one review was by the Incontinence Group. Zero authors were from LMICs. Countries with the highest representation of co-authors were the US (24.1%), UK (25.3%), Germany (23.5%), South Korea (6.8%), Australia (6.2%), Netherlands (3.7%), China (2.8%), Canada (2.5%), Brazil (1.5%). Gender could be ascertained for 94.14% (N=305/324) of co-authors. Women made up 27.5% (N=84/305) of co-authors, 16.0% (N=8/50) of first authors, and 16.89% (N=9/53) of corresponding authors. Conclusions: Women are well-represented in Cochrane Reviews related to genitourinary cancers compared to urology-specific journals and their representation in urology. However, LMICs contributed zero authors, while those from the US, UK, and Germany constitute >70% of authors for one of the highest-quality evidence sources in urology. Equitable authorship representation may help expand both the utilization and the global relevance of recommendations of such high-impact urology literature. Global capacity-building efforts are warranted, particularly in Africa, for enhancing the involvement of LMIC urologists with evidence synthesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.117 | 0.529 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.068 | 0.092 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".