How are we ‘doing’ cultural diversity? A look across English Canadian undergraduate medical school programmes
Bibliographic record
Abstract
BACKGROUND: Cultural diversity education is a required curriculum component at all accredited North American medical schools. Each medical school determines its own content and pedagogical approaches. AIM: This preliminary study maps the approaches to cultural diversity education in English Canadian medical schools. METHODS: A review of 14 English Canadian medical school websites was undertaken to identify the theoretical approaches to cultural diversity education. A PubMed search was also completed to identify the recent literature on cultural diversity medical education in Canada. Data were analysed using 10 criteria that distinguish pedagogical approaches, curricular structure, course content and theoretical understandings of cultural diversity. RESULTS: Based on the information posted on English Canadian medical school websites, all schools offer cultural diversity education although how each 'does' cultural diversity differs widely. Two medical schools have adopted the cultural competency model; five have adopted a critical cultural approach to diversity; and the remaining seven have incorporated some aspects of both approaches. CONCLUSIONS: More comprehensive research is needed to map the theoretical approaches to cultural diversity at Canadian medical schools and to evaluate the long-term effectiveness of these approaches on improving physician-patient relationships, reducing health disparities, improving health outcomes and producing positive learning outcomes in physicians.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".