Redesigning a Resident Program Evaluation to Strengthen the Canadian Residency Education Accreditation System
Bibliographic record
Abstract
Accreditation is an essential tool to ensure quality postgraduate medical education (PGME) in Canada (also known as residency or graduate medical education in the United States). Residents participate in the accreditation process of residency training programs in Canada primarily through three steps: completing a resident program evaluation (RPE), meeting with the surveyors during on-site visits, and participating as members of the surveyor team.The author first provides a brief description of the current state of the Canadian PGME system, examining how it connects to the existing accreditation system for residency training programs. The article describes the process that was undertaken to develop and implement a new set of RPEs informed by medical education principles, as well as the development of a new information package about the accreditation process for residents.Through a multistage, consultative and iterative process, a draft RPE was developed and reviewed by various groups and was eventually implemented at a full on-site survey. At each stage, the feedback was used to further refine and revise the RPE before moving to a subsequent stage. These consultations were to ensure both face and content validity of the tools.This new RPE is one component of a new accreditation survey package that will be used to determine the residents' perspectives on their training program and to educate them on the importance of accreditation in ensuring quality PGME.
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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 | 0.183 | 0.163 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".