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Record W4390796889 · doi:10.1080/0142159x.2023.2298763

Advancing anti-oppression and social justice in healthcare through competency-based medical education (CBME)

2024· article· en· W4390796889 on OpenAlexaff
Jamiu O. Busari, Linda Diffey, Karen E. Hauer, Kimberly D. Lomis, Jonathan M. Amiel, Michael Barone, Karen Schultz, H. Carrie Chen, Arvin Damodaran, David Turner, Benjamin Jones, Ivy Oandasan, Ming‐Ka Chan

Bibliographic record

VenueMedical Teacher · 2024
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsToronto General HospitalQueen's UniversityChildren's Hospital of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsOppressionSocial justiceEquity (law)Medical educationContext (archaeology)MedicinePsychologyPedagogyPolitical science

Abstract

fetched live from OpenAlex

Competency-based medical education (CBME) focuses on preparing physicians to improve the health of patients and populations. In the context of ongoing health disparities worldwide, medical educators must implement CBME in ways that advance social justice and anti-oppression. In this article, authors describe how CBME can be implemented to promote equity pedagogy, an approach to education in which curricular design, teaching, assessment strategies, and learning environments support learners from diverse groups to be successful. The five core components of CBME programs - outcomes competency framework, progressive sequencing of competencies, learning experiences tailored to learners' needs, teaching focused on competencies, and programmatic assessment - enable individualization of learning experiences and teaching and encourage learners to partner with their teachers in driving their learning. These educational approaches appreciate each learner's background, experiences, and strengths. Using an exemplar case study, the authors illustrate how CBME can afford opportunities to enhance anti-oppression and social justice in medical education and promote each learner's success in meeting the expected outcomes of training. The authors provide recommendations for individuals and institutions implementing CBME to enact equity pedagogy.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.606
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
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 integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.399
Teacher spread0.381 · 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

Citations18
Published2024
Admission routes1
Has abstractyes

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