Comparing the Performance in Family Medicine Residencies of Graduates From Longitudinal Integrated Clerkships and Rotation-Based Clerkships
Bibliographic record
Abstract
PURPOSE: In 2008, the University of Calgary implemented a longitudinal integrated clerkship (LIC) called the Rural Integrated Community Clerkship (RICC), which places students in a rural community for 32 weeks. Research indicates that LIC students perform academically as well as or better than students completing rotation-based clerkships (RBCs). However, little is known about how LIC graduates perform in residency. This study compared residency program director ratings of RICC and RBC graduates. METHOD: The performance of RICC and RBC graduates (2009-2011) was assessed using a rating form mailed to family medicine residency program directors at the end of graduates' first postgraduate year. Because of sample size and confounding effects of discipline, only the performance of graduates training in family medicine was examined. Data were analyzed using factor analysis, ANOVA, and chi-square. RESULTS: Three hundred sixteen of 399 (80.8%) rating forms were returned. The instrument contained two factors (clinical acumen and human sensitivity) of acceptable reliability (≥ 0.90) plus an overall rating of performance. Of 124 (31.7%) students who matched to family medicine, 101 (81.5%) rating forms (RICC = 22/25; RBC = 79/99) were returned. Program directors rated the performance of RICC graduates to be at least equivalent to their RBC peers on both dimensions. On overall performance, 16/22 (72.7%) RICC graduates and 43/79 (54.4%) RBC graduates were rated as "stronger" or "much stronger" than most residents in the program, P = .30. CONCLUSIONS: The performance of RICC graduates was at least equivalent to the performance of their RBC peers.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".