Characteristics of Interim Deans at U.S. Medical Schools
Bibliographic record
Abstract
Purpose: To provide a baseline, descriptive understanding of individuals serving as interim deans at U.S. medical schools. Over the past quarter century, roughly 9% to 16% of all medical school deans were serving as interim leaders. This research reviews demographic characteristics, how long they served, and the impact of having served on one's likelihood of serving as a permanent dean.\nMethod: The Association of American Medical Colleges' Council of Deans national database was the data source for this study. The authors reviewed counts and information by year for academic years 1989-1990 through 2014-2015 to yield a snapshot of interim dean counts. The authors analyzed data by demographic characteristics-namely, sex, race/ethnicity, degree, specialty, and years of service-and compared data with those of permanent deans. Descriptive statistics are presented.\nResults: Overall, between 14 and 27 individuals served as interim deans during each academic year in this study (9%-16% of all unique individuals with a dean or interim dean appointment). Of all individuals serving as interim deans in this time frame, 88% were men (228/259) and 86% were white (222/259). The average time in the interim dean role was roughly 13 months, and a high percentage went on to serve as permanent deans (ranging from 15% to 63%).\nConclusion: The results of this study add detail to the collective understanding of these leaders in medical schools. The authors discuss how individuals and institutions can facilitate success and preparedness for an interim dean appointment.
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.
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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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".