Advancing Global Health Equity: The Role of the Liberal Arts in Health Professional Education
Bibliographic record
Abstract
Much innovation has taken place in the development of medical schools and licensure exam processes across the African continent. Still, little attention has been paid to education that enables the multidisciplinary, critical thinking needed to understand and help shape the larger social systems in which health care is delivered. Although more than half of medical schools in Canada, the United Kingdom, and the United States offer at least one medical humanities course, this is less common in Africa. We report on the "liberal arts approach" to medical curricula undertaken by the University of Global Health Equity beginning in 2019. The first six-month semester of the curriculum, called Foundations in Social Medicine, includes courses in critical thinking and communication, African history and global political economy, medical anthropology and social medicine, psychology and health, gender and social justice, information technology and health, and community-based training. Additionally, an inquiry-based pedagogy with relatively small classes is featured within an overall institutional culture that emphasizes health equity. We identify key competencies for physicians interested in pursuing global health equity and how such competencies relate to liberal arts integration into the African medical school curriculum and pedagogical approach. We conclude with a call for a research agenda that can better evaluate the impact of such innovations on physicians' education and subsequent practices.
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.027 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".