Evidence of Differential Attainment in Canadian Medical School Admissions: A Scoping Review
Bibliographic record
Abstract
PURPOSE: In Canada, many groups (e.g., Black, Indigenous, rural backgrounds) have historically faced and continue to encounter systemic barriers in accessing the medical profession. These barriers often manifest in performance disparities, known as differential attainment, during medical school admissions. This scoping review summarizes the nature and extent of evidence on the association of differential attainment in medical school admissions selection tools and outcomes with applicant social identity in the Canadian context. METHOD: The authors used Arksey and O'Malley's scoping review framework to summarize research studies published between 2000 and 2022 with empirical evidence of differential attainment in admissions selection tools and outcomes with respect to a range of applicant social identity categories. The authors recorded whether studies adopted a structuralist and/or intersectional perspective. RESULTS: Ultimately, 15 studies were included in the review. While the evidence on differential attainment associated with social identity in Canadian medical education was heterogeneous, numerous studies highlight differential attainment in the admissions process associated with applicant race and/or ethnicity (6 studies), age (5 studies), gender (4 studies), socioeconomic status (3 studies), geographic location (4 studies), and rural or urban background (5 studies). These attainment differences were reported at 3 phases of the admissions process (invitation to interview, offer of admission, and acceptance of offer) and were driven by several admissions selection tools, including grade point average, Medical College Admission Test score, and interview performance. CONCLUSIONS: The review highlights evidence that suggests systemic, structural inequities in admissions systems manifest as differential attainment in Canadian medical school admissions. Based on this evidence, those who identify as Black or Indigenous and those with low socioeconomic status or rural backgrounds were generally more adversely affected. Admission practices must be studied and improved so medical education systems can better avow equality and human dignity and achieve equity goals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.030 | 0.045 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".