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Record W2183599874

Critical pedagogy as a means to achieving social accountability in medical education

2015· article· en· W2183599874 on OpenAlexaff
Brian Ross

Bibliographic record

Venue˜The œinternational journal of critical pedagogy · 2015
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsNOSM UniversityLakehead University
Fundersnot available
KeywordsAccountabilityTransformative learningIdeologySocial accountingPublic relationsCurriculumHealth careSocial justiceSociologyPolitical sciencePedagogySocial scienceLawManagementEconomicsPolitics
DOInot available

Abstract

fetched live from OpenAlex

Varied social, economic, environmental, and geographic factors lead to often avoidable differences in health between various groups and populations.  The reform of health care systems is key to reducing such ‘health inequity’ including the fair provision of timely high-quality healthcare to all members of society.  The education of health providers themselves has a crucial role to play in the transformative change required to achieve this but, in the case of physicians, has been ineffective in doing so.  An ideological movement is emerging, however, in medical education, that of social accountability which requires that medical schools further the enhancement of the health of the entire society it is part of rather than being interested in furthering the narrow aims of the medical establishment.  The question is how to go about altering medical curricula in furtherance of social accountability.  In this paper I argue that critical pedagogy provides an established framework for doing so which can be used to guide those interested in making medical education a force for social justice.

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)0.004
metaresearch head score (Gemma)0.038
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient 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: Empirical
Teacher disagreement score0.457
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.050
GPT teacher head0.500
Teacher spread0.451 · 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
Published2015
Admission routes1
Has abstractyes

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