Innovation-Oriented Medical School Curricula: Review of the Literature
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
Innovation and entrepreneurship (I&E) programs in medical education have become available as medical schools recognize the need to train forward-thinking physicians. There is considerable diversity in the design and implementation of these curricula, which represents a challenge and possibly serves as a deterrent for the development of additional I&E programs. A comprehensive search of medical school I&E programs and review of all Association of American Medical Colleges member websites (n = 171) were conducted. This review sought to (1) identify all American and Canadian allopathic medical schools with I&E curricula, (2) evaluate their structure/integration in the context of medical education, (3) outline core learning themes, and (4) describe the evaluative metrics. Information was collected through published or publicly available websites and through a questionnaire sent to identified I&E program leaders. Twenty-eight I&E-oriented medical education programs were identified from 26 schools; all of the programs integrated faculty leadership with backgrounds in medicine, engineering, and/or business/entrepreneurship. Of the programs, 57% (16/28) had been launched within the past four years and 75% (21/28) based program enrollment on a selective application process. Nearly all (27/28) incorporated lecture series and/or hands-on modules as a teaching technique. The most prevalent metric was completion of a capstone project (22/28; 79%). At least 15.2% (26/171) of American and Canadian allopathic medical schools include the option for students to participate in an I&E curriculum-based program. This review can be used to help medical school faculty with developing I&E curricula.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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