Gender Representation on North American Ophthalmology Societies' Governance Boards
Bibliographic record
Abstract
Abstract Purpose We examined the gender distribution and academic productivity of North American ophthalmology societies' board members. Methods Cross-sectional and retrospective study of board members on American and Canadian ophthalmology societies. In December 2022, data was gathered from society webpages, online archives, and the Scopus database for publication information. Results Of the identified 73 board presidents and 876 other board members, 49 (67.1%) board presidents were men and 24 (32.9%) were women, while 554 (63.2%) other board members were men and 322 (36.8%) were women (p = 0.53). Overall, board members who were men had significantly higher median h-indexes (men vs. women: 10 [interquartile range [IQR] = 22] vs. 7 [IQR = 12], p = 0.03) and median publication numbers (men vs. women: 23 [IQR = 84] vs. 14 [IQR = 52.3], p = 0.01). However, m-quotients (h-index divided by length of academic career) were not significantly different (men vs. women: 0.46 [IQR = 0.74] vs. 0.50 [IQR = 0.55], p = 0.67). Overall, a significant increase in the proportion of women board presidents comparing periods 1942 to 1961 and 2002 to 2021 was observed for all societies combined (3.1% [2/65] to 23.6% [210/888], p < 0.001). Conclusion The fraction of women on the academic boards in North American ophthalmology societies has increased sevenfold over the past 83 years. The gender composition of ophthalmology society boards is consistent with the gender composition of practicing ophthalmologists in the United States. Women in board or society positions have comparable academic output to men. Existing and new efforts to sustain progress in promoting women's representation and leadership opportunities must continue.
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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 | 0.002 | 0.010 |
| 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 | 0.000 | 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".