Research productivity and gender of research award recipients in international ophthalmology societies
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to assess the research productivity and gender of award recipients of ophthalmology research awards in international societies. METHODS: This is a retrospective, observational study. The study population included award recipients of research awards from 36 ophthalmologic societies (listed on the International Council of Ophthalmology database) in 99 years (1922-2021). A gender-specific pronoun and a photograph of each award recipient were extracted from professional websites to assign their gender. Research productivity levels were retrieved from the Elsevier Scopus author database. The main outcome measures were gender distribution of award recipients per year, mean h-index per year, mean m-quotient per year, mean h-index by society, and mean m-quotient by society. RESULTS: Out of 2506 recipients for 122 awards, 1897 (75.7%) were men and 609 (24.3%) were women. The proportion of woman recipients increased from 0% in 1922 to 41.0% in 2021. Compared with 2000-2010 (19.8%, 109 of 550), women received a greater proportion of awards (48.4%, 459 of 949) in the last decade, from 2011 to 2021. Furthermore, men more often had greater h-index scores and m-quotient scores. CONCLUSIONS: Women received awards (24.3%) at a lower rate than men (75.7%) while also exhibiting lower productivity, supporting the existence of a gender disparity. Our study found that women are under-represented in research awards, and further investigation into award selection processes and gender membership data is recommended.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".