Examination outcomes and work locations of international medical graduate family medicine residents in Canada.
Bibliographic record
Abstract
OBJECTIVE: To describe the postgraduate medical education (PGME) examination outcomes and work locations of international medical graduates (IMGs); and to identify differences between Canadians studying abroad (CSAs) and non-CSAs. DESIGN: Cohort study using data from the National IMG Database and Scott's Medical Database. SETTING: Canada. PARTICIPANTS: All IMGs who had first entered a family medicine residency program between 2005 and 2009, with the exclusion of US graduates, visa trainees, and fellowship trainees. MAIN OUTCOME MEASURES: We examined 4 outcomes: passing the Medical Council of Canada Qualifying Examination Part 2 (MCCQE2), obtaining Certification in Family Medicine (CCFP), working in Canada within 2 years of completing PGME training, and working in Canada in 2015. RESULTS: Of the 876 residents in the study, 96.1% passed the MCCQE2, 78.1% obtained a specialty designation, 37.7% worked in Canada within 2 years after their PGME, and 91.2% worked in Canada in 2015. Older graduates were more likely (odds ratio [OR] = 3.45; 95% CI 1.52 to 7.69) than recent graduates were to pass the MCCQE2, and residents who participated in a skills assessment program before their PGME training were more likely (OR = 9.60; 95% CI 1.29 to 71.63) than those who had not were to pass the MCCQE2. Women were more likely (OR = 1.67; 95% CI 1.20 to 2.33) to obtain a specialty designation than men were. Recent graduates were more likely (OR = 1.36; 95% CI 1.03 to 1.79) than older graduates were to work in Canada following training. Residents who were eligible for a full licence were more likely (OR = 3.72; 95% CI 2.30 to 5.99) to work in Canada in 2015 than those who were not eligible for a full licence were. CONCLUSION: While most IMGs who entered the family medicine PGME program passed the MCCQE2, 1 in 5 did not obtain Certification. Most IMG residents remain in Canada. Canadians studying abroad and non-CSA IMGs share similar examination success rates and retention rates.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".