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Record W4403509531 · doi:10.1080/0142159x.2024.2412098

Instilling social accountability into the health professions education curriculum with international case studies: AMEE Guide No. 175

2024· article· en· W4403509531 on OpenAlexaff
Mohamed Elhassan Abdalla, Mohamed H. Taha, David Onchonga, Robyn Preston, Cassandra Barber, Lionel Green‐Thompson, David Taylor, Erin Cameron, Robert Woollard, Charles Boelen

Bibliographic record

VenueMedical Teacher · 2024
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of British ColumbiaNOSM UniversityWestern University
FundersWorld Health Organization
KeywordsAccountabilityCurriculumHealth professionsSocial accountingMedical educationPolitical sciencePublic relationsMedicinePsychologyPedagogyHealth careBusinessLawAccounting

Abstract

fetched live from OpenAlex

This AMEE guide focuses on instilling social accountability (SA) concept and values into health professions education (HPE) curricula with the goal of producing competent, compassionate healthcare professionals who can act as change agents within the healthcare system. By incorporating SA, HPE schools will instil in their students a strong sense of accountability for addressing the health needs of the communities they serve. This AMEE guide presents a comprehensive framework for embedding SA into the HPE curriculum, covering various aspects in curriculum design, implementation, and evaluation. It also includes case studies of exemplary socially accountable curricula, highlighting the experiences of schools aspiring for SA. Acknowledging how curriculum is embedded in a larger institutional structure, and that SA requires institutional commitment in its governance structure and policies is also a critical component for consideration.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.468
Teacher spread0.431 · 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
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

Citations17
Published2024
Admission routes1
Has abstractyes

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