What is the gender representation in authorship in later phase systemic clinical trials in biliary tract cancer (BTC)? - a retrospective review of the published literature
Bibliographic record
Abstract
OBJECTIVES: Female physicians in medicine are increasing, but disparities in female authorship exist. The aim of this study was to characterise factors associated with female first (FF) and female senior (SF) authorship in later phase systemic oncological clinical trials in biliary tract cancer (BTC) and identify any changes over time. SETTING: tests and log regression were used (assessed factors associated with FF and SF authorship, including changes over time (STATA V.16)). PRIMARY OUTCOME MEASURE: FF and SF authorship in later phase systemic oncological clinical trials in BTC. SECONDARY OUTCOME MEASURE: Any changes over time? RESULTS: Of 501 publications, 163 met inclusion criteria. The median percentage of female author representation in publications was 25%; there were no female authors in 13% of publications. Geographic location of the home institution of the first and senior authors was Asia (42%/42%), Europe (29%/29%), USA (24%/22%) and other (4%/6%), respectively. Overall, FF and SF author representation was 20% and 10%, respectively. The median position of the first female author was second in all the publication author lists. The phase of trial, journal-impact factor, industry funding or whether the study met its primary endpoint did not impact FF/SF author representation. More SF authors had home institutions in 'other' geographic locations (40% in 10 trials) (p=0.02) versus Asia (6%), Europe (8%) and USA (14%). There were no significant changes in FF/SF representation over time (p=0.61 and p=0.33 respectively). CONCLUSIONS: FF and SF author representation in later phase systemic clinical trial publications in BTC is low and has not changed significantly over time. The underlying reasons for this imbalance need to be better understood and addressed.
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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 | 0.035 | 0.148 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".