Gender disparity among top North American medical schools and their affiliated radiology departments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: This study aimed to evaluate the degree of gender disparity in leadership positions at the top 25 medical schools in North America compared to their affiliated radiology departments. METHODS: The academic rank and leadership appointment of medical school and radiology faculty were obtained from publicly available official websites between June-November 2022. Gender was determined using self-identified pronouns on website biographies. Alternatively, gender API software was used. Finally, SCOPUS Elsevier was used to extract research output metrics including publication counts, citations, and h-indices. Statistical analysis was conducted using the IBM SPSS Statistics version 25 software. RESULTS: = 0.143, p < 0.001) regardless of affiliation (medical school leadership versus radiology faculty); this disparity was largest at the highest academic ranks. Male gender was associated with higher research productivity relative to female gender regardless of affiliation (p < 0.001). There were minimal statistical differences in leadership positions between genders, however the proportion of men holding the position of dean was two times higher than women. CONCLUSION: The underrepresentation of women in academic medicine is prevalent in the top-ranking medical institutions in North America and disproportionately involves senior academic ranks and leadership positions.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it