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Record W3160005136 · doi:10.46747/cfp.6705357

Assessing undergraduate medical education through a generalist lens

2021· review· en· W3160005136 on OpenAlexafffundvenueabout
Melissa Nutik, Nicole N. Woods, Azadeh Moaveni, J.A. Owen, Jared Gleberzon, Ruby Alvi, Risa Freeman

Bibliographic record

VenueCanadian Family Physician · 2021
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsDystonia Medical Research Foundation CanadaCollege of Family Physicians of CanadaUniversity of TorontoUniversity Health NetworkThe Wilson CentreSinai Health System
FundersDepartment of Family and Community Medicine, University of TorontoUniversity of Toronto
KeywordsAccreditationCurriculumGeneralist and specialist speciesMedical educationUndergraduate educationMedicinePedagogyPsychologyEcology

Abstract

fetched live from OpenAlex

PROBLEM BEING ADDRESSED: Medical schools aim to integrate the values of generalism into their undergraduate programs. However, currently no program has been described to measure the degree to which formal curricular materials represent generalist principles. OBJECTIVE OF PROGRAM: To quantify the generalism principles present in undergraduate medical education learning materials and to provide recommendations to enhance generalism content. PROGRAM DESCRIPTION: A review of the literature and accreditation documents was conducted to identify key elements of medical generalism. An evidence-informed tool, the Toronto Generalism Assessment Tool, was developed and applied to the new preclerkship undergraduate cases at the University of Toronto in Ontario. The findings regarding the presence of generalism principles and recommendations to enhance generalism content were provided to case developers. The recommendations were valued and were incorporated into subsequent iterations of the cases. CONCLUSION: This is the first report of a successful evidence-informed program to assess the degree of generalism reflected in undergraduate medical education curricular documents. This program can be used by other institutions wishing to review their curricula through a generalist lens.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.090
GPT teacher head0.406
Teacher spread0.316 · 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
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

Citations9
Published2021
Admission routes4
Has abstractyes

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