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Teaching Professionalism

2006· review· en· W2004428428 on OpenAlexaff
Richard L. Cruess

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2006
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineProcess (computing)Medical educationReflection (computer programming)Subject (documents)Tacit knowledgeEngineering ethicsKnowledge management

Abstract

fetched live from OpenAlex

Professionalism as a subject must be taught explicitly. This requires an institutionally accepted definition which then must be learned by both students and faculty. This directs what will be taught, expected, and evaluated. Of equal importance, and more difficult to achieve, is the incorporation of the values and attitudes of professionalism into the tacit knowledge base of physicians in training and in practice. This requires learning experiences which encourage self-reflection on professionalism throughout the continuum of medical education. Because of the great influence of role models and because most physicians do not fully understand professionalism and the obligations required to sustain it, faculty development is essential to the success of any program on professionalism. Also important are strong institutional support including adequate resources, the presence of a longitudinal program which ensures repeated exposure throughout the educational process, a supportive environment, and a system of evaluation which reinforces teaching.

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)0.016
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.013
Insufficient payload (model declined to judge)0.0000.000

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 head0.332
GPT teacher head0.620
Teacher spread0.288 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations85
Published2006
Admission routes1
Has abstractyes

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