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Record W2945771230 · doi:10.35301/ksme.2007.10.1.9

Medical Ethics Education in North-American Medical Schools

2007· article· en· W2945771230 on OpenAlexaboutno aff
Yoo-Seock CHEONG

Bibliographic record

VenueKorean Journal of Medical Ethics · 2007
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
Fundersnot available
KeywordsMedical ethicsCurriculumMedical educationMilitary medical ethicsEngineering ethicsNursing ethicsInformation ethicsWork (physics)MedicinePolitical scienceSociologyPedagogyLawEngineering

Abstract

fetched live from OpenAlex

Medical schools in the United States and Canada now include medical ethics education as an essential part of their curricula. Despite this, recent studies point to deep shortcomings in the literature on medical ethics education. Deficits exist in all areas of the literature: in the theoretical work done on the overall goals of medical ethics education, in the empirical studies that attempt to examine outcomes for students, and in the studies evaluating the effectiveness of various teaching methods. This article summarizes the main findings of three important articles concerning medical ethics education that were originally published in the journal Academic Medicine. This article also discusses the implications of these findings for medical ethics education in Korea. It is argued that further progress in medical ethics education may depend on the willingness of medical schools to devote more curricular time and funding to medical ethics.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.114
GPT teacher head0.559
Teacher spread0.445 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2007
Admission routes1
Has abstractyes

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