Cross-Cultural Undergraduate Medical Education in North America: Theoretical Concepts and Educational Approaches
Bibliographic record
Abstract
BACKGROUND: Cross-cultural undergraduate medical education in North America lacks conceptual clarity. Consequently, school curricula are unsystematic, nonuniform, and fragmented. This article provides a literature review about available conceptual models of cross-cultural medical education. The clarification of these models may inform the development of effective educational programs to enable students to provide better quality care to patients from diverse sociocultural backgrounds. SUMMARY: The approaches to cross-cultural health education can be organized under the rubric of two specific conceptual models: cultural competence and critical culturalism. The variation in the conception of culture adopted in these two models results in differences in all curricular components: learning outcomes, content, educational strategies, teaching methods, student assessment, and program evaluation. CONCLUSIONS: Medical schools could benefit from more theoretical guidance on the learning outcomes, content, and educational strategies provided to them by governing and licensing bodies. More student assessments and program evaluations are needed in order to appraise the effectiveness of cross-cultural undergraduate medical education.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".