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Record W4241665367 · doi:10.31219/osf.io/u47nb

Abraham Flexner’s Lasting Effects on Medical Education in the United States and Canada

2021· preprint· en· W4241665367 on OpenAlexaboutno aff
Julie H. Schiavo

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsDemographicsMedical educationFoundation (evidence)Medical schoolPolitical scienceQuality (philosophy)MedicineSociologyLaw

Abstract

fetched live from OpenAlex

In 1910, a document produced by an American educator changed the course of medical education ushering in a new philosophy based on the scientific method, active learning, and competency-based education. Abraham Flexner’s report, Medical Education in the United States and Canada: A Report to the Carnegie Foundation for the Advancement of Teaching, was a groundbreaking study undertaken to improve the quality of medical education and ensure capable, competent physicians and surgeons in the United States and Canada. However, the Flexner Report was not without consequences, both intended and unintended. A large majority of schools examined by Flexner did not meet the standards by which he judged them. Nearly half of the schools in the report closed; most of those were programs dedicated to medical education for African Americans, women, and working-class students changing the demographics of the medical profession in ways that it has only recently begun to remedy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.469

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0260.010
Scholarly communication0.0110.004
Open science0.0020.006
Research integrity0.0060.013
Insufficient payload (model declined to judge)0.0160.002

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.

Opus teacher head0.011
GPT teacher head0.327
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations2
Published2021
Admission routes1
Has abstractyes

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