Sticky Floor and Glass Ceilings in Academic Medicine: Analysis of Race and Gender
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 paper examines the changes in the representation of women and racial minorities in academic medicine, compares the proportion of minorities in medicine and the general United States (US) population, and discusses potential explanations for observed trends. Methods A retrospective cross-sectional analysis of the Association of American Medical Colleges (AAMC) database was done and used to collect data on the gender and race of physicians in academic medicine. Data was collected for instructors, assistant professors, associate professors, full professors, and chairpersons from 2007 to 2018, and trends were presented. Results White physicians represented most academic physicians at every academic level, peaking in proportion at 82.74% of chairpersons and were lowest at the level of instructor at 59.30%. A similar distribution existed when gender was compared, with men comprising 84.67% of chairpersons and forming the majority at levels of full, associate, and assistant professors. However, most physicians at the level of instructors are women at 55.44%. Conclusions Though women and racial minorities have gained greater representation in academic medicine over the past decade, high-level academic positions are not as accessible to them. Existing efforts of advocacy for women and minority races have proven fruitful over the past decade, but much more work needs to be done.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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