Qualitative evaluation of the contribution of CanMEDS roles in the development of area of focused competence diplomas
Bibliographic record
Abstract
Background: While many Area of Focused Competency (AFC) Diplomas are available to those who have completed Pediatric residency training, it is not known which competencies are enhanced within each AFC discipline. Our objective was to determine which CanMEDS roles were targeted by existing AFCs available to those who have completed Pediatric residency training and identify gaps within CanMEDs roles that may be fulfilled by the development of new AFCs. Methods: A qualitative study was undertaken using document analysis methodology to compare CanMEDS competencies across AFCs available to those with Royal College examination eligibility or certification in Pediatrics. RCPSC Competency Training Requirements documents were used to compare and contrast the competencies in each AFC with competencies established in Pediatric residency training. Key and Enabling Competencies were compared for each CanMEDS role to identify differences. Results: Ten AFCs were identified with eligibility requirements including Royal College examination eligibility or certification in Pediatrics. All 10 AFCs included at least one new Medical Expert competency, for a total of 42 unique competencies in this role across all AFCs. The Scholar role had only 10 new competencies across seven AFCs, while only one AFC added a single unique competency in the Collaborator role. Conclusions: The majority of new competencies contributed by AFCs lie within the CanMEDS role of Medical Expert. The Scholar and Collaborator roles have the least differences when comparing competencies of existing AFCs to those competencies established in Pediatric residency training. Developing additional AFCs that offer advanced skills in these roles may help close this gap within the discipline of Pediatrics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".