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The ABCs of pedagogy for clinical teachers

2003· article· en· W2047334060 on OpenAlexaff
Peter J. McLeod, Yvonne Steinert, Tim Meagher, Audrey McLeod

Bibliographic record

VenueMedical Education · 2003
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsDelphi methodMedical educationProcess (computing)PsychologyClinical PracticeDelphiCurriculumMedicinePedagogyComputer scienceNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Clinical teachers rarely receive formal instruction in the basic concepts and principles of education. It is usually assumed that expertise as a practitioner will translate into effectiveness as a teacher. PURPOSE: To identify the important concepts and pedagogic principles, which, if known and understood by clinical practitioners, might enhance their teaching prowess and success. METHOD: We developed a long list of potentially important concepts identified in the education literature. We then conducted a 3-round Delphi expert opinion-soliciting process to identify which of the concepts were of most importance to clinical teachers. RESULTS: Thirteen of the 14 panel members successfully completed the process and achieved 94% reliability in rating the potential importance of the concepts on the e-mailed ratings list. CONCLUSION: We have identified a limited list of core pedagogic concepts, knowledge of which may enhance the success of clinical teachers.

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)0.035
metaresearch head score (Gemma)0.090
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: none
Teacher disagreement score0.035
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.090
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0050.019
Scholarly communication0.0100.006
Open science0.0010.007
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0070.002

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 head0.048
GPT teacher head0.513
Teacher spread0.466 · 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

Citations91
Published2003
Admission routes1
Has abstractyes

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