Do Canadian Medical Licensing Exam Scores Correlate with Physicians’ Future Performance in Practice? A Cohort Study of Alberta Family Physicians
Why this work is in the frame
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Bibliographic record
Abstract
Background:. Medical licensing examinations are cornerstones that uphold a standardized level of competence among practicing physicians. There are voices that contend the validity of such examinations as accurate measures of physician competency, viewing them as barriers to practice. Research into the predictive efficacy of licensing exams in Canada is still nascent. We attempt to remedy this.Methods:. We conducted a historical cohort study of potential factors, including licensing examinations, which might correlate with complaints against family physicians in Alberta using Medical Council of Canada (MCC) and College of Physicians and Surgeons of Alberta (CPSA) data. Logistic regression was used to identify factors associated with non-dismissed complaints (NDCs).Results:. The analyses indicated there are eight NDC predictors, among them the MCC Qualifying Examination (MCCQE) Part I. The regression model was statistically significant, X2 (8, N-539) = 54.23, P<0.0001. In our study, a decrease of one point on the total score on the first attempt is associated with a 0.6% increase in the odds of the physician having an NDC.Conclusion:. The higher the score received on the first MCCQE Part I attempt, the lesser the probability of NDCs in family physicians’ future practice. Our research provides compelling evidence that licensing examinations effectively gauge and predict physician performance, serving as a vital public safeguard.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it