Selection of international medical graduates into postgraduate training positions in Canada. Who applies? Who is selected?
Bibliographic record
Abstract
Background: International medical graduates (IMGs) are an essential part of the Canadian physician workforce. Considering current pressures on the health care system, an update regarding application numbers and match rates for IMGs to postgraduate positions in Canada is needed. Methods: We conducted a quantitative cross-sectional study to explore the characteristics of IMGs who are currently applying to the Canadian Residency Matching Service (CaRMS) positions to gain a broad understanding of the composition of this group and the factors associated with successful matching. Results: Out of 1,725 applicants in 2019, 14.1% matched on the first attempt and 6.4% after two to three attempts. Only 22.7% matched with a position (57.6% women). Applicants submitted an average 19.6 site/program applications. The percentage of IMGs matched did not statistically differ by gender. The relationship between the year of graduation or geographic area of medical school qualified and matching was significant for the first and second iterations, with current-year graduates and Oceania/Pacific Islands applicants more likely to match. Conclusions: This study provided us with accurate numbers and information about the Canadians studying abroad and IMG groups applying, and factors associated with being matched to the IMG positions through CaRMS, which will be instrumental in informing future selection implications for Canada.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.038 | 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".