Gender and research productivity of award recipients among Canadian national ophthalmology and affiliate subspecialty societies
Bibliographic record
Abstract
Background:Although women remain historically underrepresented in medical achievement awards, gender distribution of award recipients in ophthalmology in Canada remain to be explored based on research productivity metrics.Objective:To characterize the gender distribution of award recipients among the main Canadian national ophthalmological societies and subspecialty affiliates based on research productivity, graduate degrees, affiliated institution, and award type.Design:Retrospective, observational study.Methods:Award recipients were selected from the Canadian Ophthalmological Society (COS), Canadian Association of Paediatric Ophthalmology and Strabismus (CAPOS); Canadian Cornea, External Disease, and Refractive Surgery Society (CCEDRSS); Canadian Council of Ophthalmology Residents (CCOR) Research Proposal Award; and Canadian Glaucoma Society (CGS). The recipients’ gender was determined by web search for the gender-specific pronoun, profile photograph check, or using Gender-API. Outcomes included gender distribution of recipients per award, society, year, and training level and differences in research productivity.Results:Thirteen special awards were given to 255 recipients (215 individuals) from 1995 to 2022. In total, 31% of recipients were women, the majority being from Canada. Women had a significantly lower median h-index (2.0 (0–62) women versus 4.0 (0–81) men, p = 0.001) and number of published documents (3.0 (0–213) women versus 8.0 (0–447) men, p < 0.001). On stratified analyses by type of award (research or lifetime achievement) and level of training (trainee or ophthalmologist), significant differences were found for mean h-index and number of publications for awardees within the research category (p = 0.01 and p = 0.02, respectively) and trainee level (p = 0.01 and p = 0.02, respectively). Overall, women’s proportion rates in awards did not reach parity in 27 out of the 28 years analyzed.Conclusion:Women were confirmed to be historically minored in proportion among the prominent society awards in Canada, with attested research disparity possibly explaining some of this bias. These findings require further confirmation in larger cohorts accounting for additional educational, institutional, and provincial factors.Registration:Not applicable.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.000 |
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".