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Record W4386847414 · doi:10.1080/10401334.2023.2259363

Reconsidering a Global Agency for Medical Education: Back to the Drawing Board?

2023· article· en· W4386847414 on OpenAlexaff
Ahmed Rashid, Thirusha Naidu, Dawit Wondimagegn, Cynthia Whitehead

Bibliographic record

VenueTeaching and Learning in Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAgency (philosophy)Context (archaeology)EmpowermentPublic relationsPolitical scienceRepresentation (politics)Public administrationSociologyLawSocial sciencePolitics

Abstract

fetched live from OpenAlex

Issue: The World Federation for Medical Education (WFME) was established in 1972 and in the five decades that followed, has been the de facto global agency for medical education. Despite this apparently formidable remit, it has received little analysis in the academic literature. Evidence: In this article, we examine the historical context at the time WFME was established and summarize the key decisions it has taken in its history to date, highlighting particularly how it has adopted positions and programmes that have seemingly given precedence to the values and priorities of countries in the Global North. In doing so, we challenge the inevitability of the path that it has taken and consider other possible avenues that such a global agency in medical education could have taken, including to advocate for, and to develop policies that would support countries in the Global South. Implications: This article proposes a more democratic and equitable means by which a global organization for medical education might choose its priority areas, and a more inclusive method by which it could engage the medical education community worldwide. It concludes by hypothesizing about the future of global representation and priority-setting, and outlines a series of principles that could form the basis for a reimagined agency that would have the potential to become a force for empowerment and global justice in medical education.

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)0.006
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.375
Teacher spread0.324 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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