Evaluation of Residency Programs: A Novel Approach Using Simulation
Bibliographic record
Abstract
BACKGROUND: In Canada, there has been discussion about restructuring the accreditation process for residency education programs with the possibility of exempting selected programs from regular, on-site, external reviews. OBJECTIVE: We assessed the feasibility and acceptability of a structured and rigorous internal review that identified program strengths and weaknesses, with the aim of allowing well-performing programs to be exempt from external reviews or to facilitate a significant lengthening of the review cycle. METHODS: We simulated all aspects of a regular, on-site, external review. All participants (program directors, program coordinators, faculty surveyors, and resident surveyors) were trained and performed all components of a formal external review. Participants completed an online survey to assess perceptions of the process and outcome. RESULTS: The overall response rate was 73% (109 of 149). Most respondents perceived the process to be either extremely or very rigorous (84%), fair (82%), and unbiased (75%). Those with previous review experience (77%) reported that the internal review process simulated a regular, on-site, external review either well or very well (mean rating 4.87, SD 0.90). Most program directors reported the cited list of program strengths to be either extremely or very appropriate (74%, 26 of 35). Perceptions of fairness, bias, and the appropriateness of cited program strengths and weaknesses depended on review outcome. CONCLUSIONS: A structured and rigorous internal review process that simulates a regular, on-site, external review is feasible and could yield a list of program strengths and weaknesses for use in ongoing assessment and improvement.
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 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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".