Exploring Diversity in Otolaryngology-Head and Neck Surgery Journal Editorial Boards
Bibliographic record
Abstract
Objective: Despite increasing diversity in medical school entrants, disparities exist in academic leadership. This study sought to examine the proportion of women and visible minorities (VMs) among editorial board members (EBMs) of otolaryngology journals. Methods: Two reviewers collected journal, editorial board, and editor-in-chief characteristics using journal mastheads or official websites. Gender and VM representation on editorial boards and factors associated with increased representation were investigated. Results: Forty-one journals were explored, from January to April 2022. Of 2128 EBMs, 663 (31.3%) were VMs and 551 (25.9%) were women. Editor-in-chief roles were held by 12 (25%) VM individuals and 3 (6.2%) women. Gender differences in the distribution of editorial board positions were found ( P < .001); women had higher representation as associate editors (24.5%, n = 551 vs 15.4, n = 1577%) and deputy/managing editors (2.2%, n = 551 vs 0.4%, n = 1577), while men were more represented as editor-in-chief (2.9%, n = 1577 vs 0.5%, n = 551). Similar VM representation existed between genders (31.0% male; 31.6% women) ( P = .80). Journal impact factor quartile and gender were significantly correlated ( P < .001); a higher proportion of women were represented in the first (27.0% vs 24.5%) and fourth (12.0% vs 4.9%) quartile. No significant factors were identified for higher women’s editorial board representation. Larger editorial board size ( P = .002) and Asian/South American journals ( P = .003 to P < .001) had significantly higher representation of VMs. Conclusion: Women and VMs are underrepresented in high-ranking editorial positions. Diversity in editorial boards is needed to ensure fair and balanced journal reviews and equity within otolaryngology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".