Is Undergraduate Performance Predictive of Postgraduate Performance?
Bibliographic record
Abstract
BACKGROUND: The continuity of undergraduate to postgraduate training suggests that performance in medical school should predict performance later in residency. PURPOSE: The goal is to determine whether undergraduate performance is predictive of postgraduate performance. METHODS: Residency program directors assessed the performance of medical school graduates (Classes 2004-2006) at the end of the 1st postgraduate year. Measures of undergraduate performance were retrieved including grade point averages, clerkship in-training evaluation reports, and the total score on the Medical Council of Canada Part 1 exam. RESULTS: Complete data were available for 242 (81.5%) graduates. Postgraduate performance consisted of two reliable factors (clinical acumen and human sensitivity) that explained 78% of the variance. Correlations between undergraduate and the two postgraduate measures were low (.03-.31). CONCLUSIONS: Measures of undergraduate performance appear to be poor predictors of performance in residency that consisted of two primary dimensions (clinical acumen and human sensitivity).
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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 | 0.017 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".