Ready, set, go! Evaluating readiness to implement competency-based medical education
Bibliographic record
Abstract
PURPOSE: Organizational readiness is critical for successful implementation of an innovation. We evaluated program readiness to implement Competence by Design (CBD), a model of Competency-Based Medical Education (CBME), among Canadian postgraduate training programs. METHODS: framework of organizational readiness and addressed: program motivation, general capacity for change, and innovation-specific capacity. An overall readiness score was calculated. An ANOVA was conducted to compare overall readiness between disciplines. RESULTS: = 79). The mean overall readiness score was 74% (30-98%). There was no difference in scores between disciplines. The majority of respondents agreed that successful implementation of CBD was a priority (74%), and that their leadership (94%) and faculty and residents (87%) were supportive of change. Fewer perceived that CBD was a move in the right direction (58%) and that implementation was a manageable change (53%). Curriculum mapping, competence committees and programmatic assessment activities were completed by >90% of programs, while <50% had engaged off-service disciplines. CONCLUSION: Our study highlights important areas where programs excelled in their preparation for CBD, as well as common challenges that serve as targets for future intervention to improve program readiness for CBD implementation.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.106 | 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".