A92 FEMALE AUTHORSHIP IN GASTROENTEROLOGY RANDOMIZED CONTROL TRIALS: 2011 - 2021
Bibliographic record
Abstract
Abstract Background Although tremendous strides have been made in the participation of women in medicine, female continues to be underrepresented in leadership positions and higher-level academic medicine. An important factor in determining career advancement in academic medicine is the quality and quantity of an individual’s scholarly publications. To date, no study has looked at female authorship in gastroenterology (GI) randomized control trials (RCTs), which remains the gold standard for evaluating intervention effectiveness. Purpose The primary outcome is to assess female authorship in gastroenterology randomized control trials from 2011 to 2021, and the secondary outcome is to assess female authorship within GI subspecialty RCT publications. Method In this observational study, the gender of the first and last author of gastroenterology RCTs from January 1, 2011 to December 31, 2021 was assessed. Python (v3.8.12) was used to extract publication data from PubMed. A validated algorithm, genderize.io, was used to determine gender. Author first names that cannot be determined by the algorithm were manually searched on publicly-available profiles. Result(s) A total of 5690 original gastroenterology RCTs were included from January 1, 2011 to December 31, 2021. The gender of the first and senior authors of the papers was determined for 5668 (99.6%) first authors and 5656 (99.4%) senior authors. Overall, 1937 (34.1%) of the first authors and 1138 (20.0%) of senior authors were female. There was an increase in the proportion of female first authors over the past decade, from 25.4% in 2011 to 37.8% in 2021 (p<0.05). For senior authors, there was a more gradual increase in female authorship from 14.2% in 2011 to 21.6% in 2021 (p<0.05). (Figure 1) Within GI subspecialties, 612 RCTs were included for inflammatory bowel disease, 1143 RCTs were included for hepatology, and 1856 RCTs were included for therapeutic endoscopy from January 1, 2011 to December 31, 2021. Further analysis will be performed to determine the gender trend for GI subspecialties. Image Conclusion(s) Female authorship in gastroenterology RCTs has increased from 2011 to 2021, although the rate of senior authorship has increased to a slower extent compared to first authors. Across all years, female authorship in gastroenterology RCTs has been lower than males. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared
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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 | 0.156 | 0.472 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.011 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".