Perceptions of bias in the selection of international medical graduate residency applicants in Canada
Bibliographic record
Abstract
Background: In Canada, international medical graduates (IMG) consist of immigrant-IMG and previous Canadian citizens/permanent residents who attended medical school abroad (CSA). CSA are more likely to obtain a post-graduate residency position than immigrant-IMG and previous studies have suggested that the residency selection process favours CSA over immigrant-IMG. This study explored potential sources of bias in the residency program selection process. Methods: We conducted semi-structured interviews with senior administrators of clinical assessment and post-graduate programs across Canada. We asked about perceptions of the background and preparation of CSA and immigrant-IMG, methods applicants use to improve likelihood of obtaining residency positions, and practices that may favour/discourage applicants. Interviews were transcribed and a constant comparative method was employed to identify recurring themes. Results: Of a potential 22 administrators, 12 (54.5%) completed interviews. Five key factors that may provide CSA with an advantage were: reputation of the applicant's medical school, recency of graduation, ability to complete undergraduate clinical placement in Canada, familiarity with Canadian culture, and interview performance. Conclusions: Although residency programs prioritize equitable selection, they may be constrained by policies designed to promote efficiencies and mitigate medico-legal risks that inadvertently advantage CSA. Identifying the factors behind these potential biases is needed to promote an equitable selection process.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.054 | 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".