Women in Leadership Positions in Academic Cardiology: A Study of Program Directors and Division Chiefs
Bibliographic record
Abstract
BACKGROUND: Gender difference in the workplace continues to be a subject of great discussion. Cross-sectional studies demonstrate that women are often underrepresented in key leadership roles. We sought to examine the proportion of women in cardiology leadership positions and to compare the findings with the differences prevalent in the overall cardiology faculty. Furthermore, we aspired to compare the proportion of women in leadership positions to the proportion in which they entered the cardiology field. METHODS: This is a cross-sectional online study of Cardiology fellowship programs identified by American Medical Association's Fellowship and Residency Electronic Interactive Database (AMA FREIDA), conducted from March to April 2017. Data of all (n = 512) cardiology fellowship program directors as well as 69% (n = 140) cardiology division chiefs were collected. RESULTS: A lower percentage of women held the role of division chief (5% vs. 95%) and program director (14% vs. 86%). However, when compared to the proportion of women in the 1992 fellowship cohort, women were significantly overrepresented in the role of program directors, with no significant difference in representation at the level of division chief. When compared to the overall cardiology faculty, program directors had significantly more publications and were more likely to have an academic rank of full professor (40% vs. 28%) or associate professor (37% vs. 23%). Male program directors had a significantly higher number of research publications, H-index, and academic rank than their female counterparts; however, such difference was not seen at the level of division chief. CONCLUSIONS: Gender difference is present in both program director and division chief roles. However, when compared to the historical cohort, significant overrepresentation of women was seen in the program director position, while proportionate representation was seen in the division chief role.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".