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Record W1596119596 · doi:10.1017/cbo9781316178485

Teaching Medical Professionalism

2016· book· en· W1596119596 on OpenAlexaff
Richard L. Cruess, Yvonne Steinert, Sylvia R. Cruess

Bibliographic record

VenueCambridge University Press eBooks · 2016
Typebook
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsIdentity (music)Engineering ethicsProfessional developmentMedical educationPsychologyPedagogyMedicineEngineering

Abstract

fetched live from OpenAlex

This book presents ideas, evidence and guidance for those interested in using the most recent advances in knowledge about learning and human development to enhance medical education's ability to form competent, caring and publicly responsible physicians. It does this by establishing the development of a professional identity in medical students and residents as a primary goal of medical education. This new approach is emerging from experience and experiment by medical educators articulating a new way of understanding their mission. It is an optimistic book - the voices are those of the leaders, theorists and experienced practitioners who have found in this new approach a promising way to confront the challenges of a new era in medicine. It summarizes the theoretical basis of identity formation, outlines our current knowledge of how best to assist learners as they acquire a professional identity, and addresses the issue of assessment of progress towards this goal.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.026
GPT teacher head0.292
Teacher spread0.267 · 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
GenreOther

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

Citations250
Published2016
Admission routes1
Has abstractyes

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