The Teaching of Cultural Issues in U.S. and Canadian Medical Schools
Bibliographic record
Abstract
PURPOSE: Despite the importance of culture in health care and the rapid growth of ethnic diversity in the United States and Canada, little is known about the teaching of cultural issues in medical schools. The study goals, therefore, were to determine the number of U.S. and Canadian medical schools that have courses on cultural issues, and to examine the format, content, and timing of those courses. METHOD: The authors contacted the deans of students and/ or directors of courses on cultural issues at all 126 U.S. and all 16 Canadian medical schools. Using a cross-sectional telephone survey, they asked whether each school had a course on cultural sensitivity or multicultural issues and, if so, whether it was separate or contained within a larger course, when in the curriculum the course was taught, and which ethnic groups the course addressed. RESULTS: The response rates were 94% for both U.S. (118) and Canadian (15) schools. Very few schools (U.S. = 8%; and Canada = 0%) had separate courses specifically addressing cultural issues. Schools in both countries usually addressed cultural issues in one to three lectures as part of larger, mostly preclinical courses. Significantly more Canadian than U.S. schools provided no instruction on cultural issues (27% versus 8%; p = .04). Few schools taught about the specific cultural issues of the largest minority groups in their geographic areas: only 28% and 26% of U.S. schools taught about African American and Latino issues, respectively, and only two thirds of Canadian schools taught about either Asian or Native Canadian issues. Only 35% of U.S. schools addressed the cultural issues of the largest minority groups in their particular states. CONCLUSIONS: Most U.S. and Canadian medical schools provide inadequate instruction about cultural issues, especially the specific cultural aspects of large minority groups.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".