IDDF2022-ABS-0056 Authorship diversity in gastroenterology-related cochrane systematic reviews: inequities in global representation
Bibliographic record
Abstract
Background Cochrane systematic reviews are amongst the highest quality of evidence available, thereby, its conclusions often impact policy and practice globally. This study sought to determine the gender and country diversity in authorship representation in the authorship of Gastroenterology-related Cochrane systematic reviews. Methods We searched and extracted data from the Cochrane Library on 23 April 2022 using ‘topic: Gastroenterology’, and included published reviews, protocols, and withdrawn publications. We extracted authors’ details and searched online to determine their gender, attempting to capture at least one webpage demonstrating it. Authors whose gender could not be ascertained were excluded from gender-based analyses. For graphical representation, we used a chloropleth-style map. Results One hundred and six publications with a total of 545 authors were included in the current study. The leading five represented nations (IDDF2022-ABS-0056 Figure 1. Chloropleth style map showing nation wise author contribution in gastroenterology related Cochrane systematic reviews) in authorship were Canada (n=195,35.9%), United Kingdom (n=119,21.9%), Chile (n=69,12.7%), Germany (n=42,7.7%), and United States of America (n=30,5.5%). First authors were mostly represented by Canada (n=41,38.6%), followed by United Kingdom (n=26,24.5%), Chile (n=14,13.2%), Germany (n=6,5.6%), and Denmark (n=6,5.6%). India is the only country among all the low and low-middle-income countries which had authorship representation and constituted 1.1% (n=6) of all the authors. Male (n=381) to female (n=168) ratio in this study was 2.26:1 (IDDF2022-ABS-0056 Figure 2. Bar chart demonstrating gender representation in authorship). There were 78 (73.6%) male and 28 (26.4%) female first authors. Women (n=22) constituted 20.8% of all the corresponding authors. Thirty-nine (36.7%) studies had no female representation in any lead author (corresponding or first author) position. Twenty (18.8%) studies didn’t have any female authors at all. Conclusions Authors from high-income countries continue to be the largest contributors to Cochrane systematic reviews in Gastroenterology, a source of one of the highest quality evidence. There is extremely poor participation/representation of authors from low and low-middle-income countries. Gender bias is also noted, with women poorly represented both as contributors as well as lead 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 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 | 0.056 | 0.275 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.036 | 0.059 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.399 | 0.106 |
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".