Competency‐based medical education: the discourse of infallibility
Bibliographic record
Abstract
BACKGROUND: Over the last two decades, competency-based frameworks have been internationally adopted as the primary educational approach in medicine. Yet competency-based medical education (CBME) remains contested in the academic literature. We look broadly at the nature of this debate to explore how it may shape scholars' understanding of CBME, and its implications for medical education research and practice. In doing so, we deconstruct unarticulated discourses and assumptions embedded in the CBME literature. METHODS: We assembled an archive of literature focused on CBME. The archive dates from 1996, the publication year of the first CanMEDS Physician Competency Framework. We then conducted a Foucauldian critical discourse analysis (CDA) to delineate the dominant discourses underpinning the literature. CDA examines the intersections of language, social practices, knowledge and power relations to highlight how entrenched ways of thinking influence what can or cannot be said about a topic. FINDINGS: Detractors of CBME have advanced an array of conceptual critiques. Proponents have often responded with a recurring discursive strategy that minimises these critiques and deflects attention from the underlying concept of the competency-based approach. As part of this process, conceptual concerns are reframed as two practical problems: implementation and interpretation. Yet the assertion that these are the construct's primary concerns was often unsupported by empirical evidence. These practices contribute to a discourse of infallibility of CBME. DISCUSSION: In uncovering the discourse of infallibility, we explore how it can silence critical voices and hinder a rigorous examination of the competency-based approach. These discursive practices strengthen CBME by constructing it as infallible in the literature. We propose re-approaching the dialogue surrounding CBME as a starting point for empirical investigation, driven by the aim to broaden scholars' understanding of its design, development and implementation in medical education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".