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Record W1975730432 · doi:10.1097/acm.0b013e3181f12bd1

Abraham Flexner and the Era of Medical Education Reform

2010· article· en· W1975730432 on OpenAlexaboutno aff
Barbara Barzansky

Bibliographic record

VenueAcademic Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsPraiseMedical educationState (computer science)Medical schoolMedicinePolitical sciencePsychology

Abstract

fetched live from OpenAlex

Many forces, including the influential report of Abraham Flexner, acted to reform medical education in the early 20th century. Most physicians were not prepared to adopt recent advances in health care due to their poor medical training. This deficit was recognized in the 20 years before Flexner's report by several organizations, including the Illinois State Board of Health, the American Medical Association, and the Association of American Medical Colleges. Before 1910, each organization had engaged in at least one review of medical schools using defined standards and had identified many of the existing deficits. The number of medical schools already had begun to decrease, dropping from 160 in 1905 to 133 in 1910. Flexner drew heavily, but not exclusively, on the standards for medical education previously developed by other organizations. He visited 155 medical schools in the United States and Canada between December 1908 and April 1910. His 1910 report included a conceptual model of how modern medical education should be conducted and descriptions of each medical school that were explicit in both praise and censure.In the decade following the Flexner Report the number of medical schools decreased from 133 to 85. The actions of state medical licensing boards to deny recognition to poor schools sealed their fate. The remaining schools had higher entrance requirements, longer terms, and better resources. The author describes key factors that contributed to the success of the changes recommended by Flexner and others, and then posits why Flexner is still remembered.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.013
GPT teacher head0.378
Teacher spread0.365 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations72
Published2010
Admission routes1
Has abstractyes

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