MétaCan
Menu
Back to cohort

Building a Generation of Physician Advocates

2015· article· en· W960174213 on OpenAlexaffabout
Tahara D. Bhate, Lawrence C. Loh

Bibliographic record

VenueAcademic Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCurriculumMandateMedical educationVariety (cybernetics)AccountabilityCurriculum developmentMedicinePublic relationsSocial accountingPolitical sciencePedagogySociologyManagementLaw

Abstract

fetched live from OpenAlex

There is an increasing focus on the social accountability of physicians as individuals, and of medicine itself. This has led to increasing emphasis on physician advocacy from a wide variety of institutions. The physician advocacy concept is now part of the Health Advocacy competency mandated by the Royal College of Physicians and Surgeons of Canada. Despite its growing prominence, physician advocacy remains poorly integrated into current medical undergraduate curricula. The authors recommend how and why curricular reform should proceed; they focus on Canadian medical education, although they hope their views will be useful in other countries as well.The authors discuss conflicting definitions of physician advocacy, which have previously hampered curriculum development efforts, and suggest a way of reconciling the conflicts. They review current gaps in advocacy-related curricula, suggest that these can be addressed by incorporating practice-based and skills acquisition elements into current didactic teaching, and offer several strategies by which an advocacy curriculum could be implemented, ranging from small modifications to current curriculum to developing new competencies in medical education nationally.The authors present a case for making an advocacy curriculum mandatory for every Canadian medical trainee; they argue that teaching trainees how to fulfill their professional responsibility to advocate may also help them meet the social accountability mandate of medical school education. Finally, the authors explain why making the development and implementation of a mandatory, skill-based curriculum in advocacy should be a priority.

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)0.026
metaresearch head score (Gemma)0.034
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 score0.026
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0210.015
Scholarly communication0.0150.012
Open science0.0030.021
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0130.004

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 head0.107
GPT teacher head0.412
Teacher spread0.305 · 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

Citations60
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueAcademic MedicineSame topicInnovations in Medical EducationFrench-language works237,207