Abraham Flexner of Kentucky, His Report, Medical Education in the United States and Canada, and the Historical Questions Raised by the Report
Bibliographic record
Abstract
One hundred years ago, the time was right and the need was critical for medical education reform. Medical education had become a commercial enterprise with proprietary schools of variable quality, lectures delivered in crowded classrooms, and often no laboratory instruction or patient contact. Progress in science, technology, and the quality of medical care, along with political will and philanthropic support, contributed to the circumstances under which Abraham Flexner produced his report. Flexner was dismayed by the quality of many of the medical schools he visited in preparing the report. Many of the recommendations in Medical Education in the United States and Canada are still relevant, especially those concerning the physician as a practitioner whose purpose is more societal and preventive than individual and curative. Flexner helped establish standards for prerequisite education, framed medical school admission criteria, aided in the design of a curriculum introduced by the basic and followed by the clinical sciences, stipulated the resources necessary for medical education, and emphasized medical school affiliation with both a university and a strong clinical system. He proposed integration of basic and clinical sciences leading to contextual learning, active rather than passive learning, and the importance of philanthropy. Flexner's report poses several questions for the historian: How were his views on African American medical education shaped by his post-Civil War upbringing in Louisville? Was the report original or derivative? Why did it have such a large impact? This article describes Flexner's early life and the report's methodology and considers several of the historical questions.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".