Emergency Medicine Journal Editorial Boards: Analysis of Gender, H-Index, Publications, Academic Rank, and Leadership Roles
Bibliographic record
Abstract
INTRODUCTION: Our goal in this study was to determine female representation on editorial boards of high-ranking emergency medicine (EM) journals. In addition, we examined factors associated with gender disparity, including board members' academic rank, departmental leadership position, h-index, total publications, total citations, and total publishing years. METHODS: In this retrospective study, we examined EM editorial boards with an impact factor of 1 or greater according to the Clarivate Journal Citations Report for a total of 16 journals. All board members with a doctor of medicine or doctor of osteopathic medicine degree, or international equivalent were included, resulting in 781 included board members. We analyzed board members' gender, academic rank, departmental leadership position, h-index, total publications, total citations, and total publishing years. RESULTS: Gender disparity was clearly notable, with men holding 87.3% (682/781) of physician editorial board positions and women holding 12.7% (99/781) of positions. Only 6.6% (1/15) of included editorial board chiefs were women. Male editorial board members possessed higher h-indices, total citations, and more publishing years than their female counterparts. Male board members held a greater number of departmental leadership positions, as well as higher academic ranks. CONCLUSION: Significant gender disparity exists on EM editorial boards. Substantial inequalities between men and women board members exist in both the academic and departmental realms. Addressing these inequalities will likely be an integral part of achieving gender parity on editorial boards.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".