When a Canadian is not a Canadian: marginalization of IMGs in the CaRMS match
Bibliographic record
Abstract
This paper explores the marginalization experienced by International Medical Graduates (IMGs) in the Canadian Residency Matching Service (CaRMS) Match. This marginalization occurs despite all IMGs being Canadian citizens or permanent residents, and having objectively demonstrated competence equivalent to that expected of a graduate of a Canadian medical School through examinations such as the MCCQE1 and the National Assessment Collaboration OSCE. This paper explores how the current CaRMS Match works, evidence of marginalization, and ethnicity and human rights implications of the current CaRMS system. A brief history of post graduate medical education and the residency selection process is provided along with a brief legal analysis of authority for making CaRMS eligibility decisions. Current CaRMS practices are situated in the context of Provincial fairness legislation, and rationalizations and rationales for the current CaRMS system are explored. The paper examines objective indicators of IMG competence, as well as relevant legislation regarding international credential recognition and labour mobility. The issues are placed in the context of current immigration and education policies and best practices. An international perspective is provided through comparison with the United States National Residency Matching Program. Suggestions are offered for changes to the current CaRMS system to bring the process more in line with legislation and current Canadian value systems, such that "A Canadian is a Canadian."
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.098 | 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".