Beyond Borders: Building Global Health Programs at McGill University Faculty of Medicine
Bibliographic record
Abstract
Globalization has irrevocably altered the determinants of health as well as the delivery of health care. Although these changes have been increasingly recognized by governments and funding agencies, and despite the large and growing interest in global health topics among faculty and students, many medical educational programs lack courses or programs in this important area. At McGill University Faculty of Medicine, the Global Health Programs (GHP) were established to build research and training capacity in global health locally and internationally, to stimulate individuals to work in related fields and topics, and to facilitate partnerships with institutions around the world. These goals are addressed through programs that foster communication among interested faculty and students; provide resources such as project databases and easily accessed, centrally located reference materials; and provide both financial and consultative support for faculty and student initiatives. Important lessons learned in building GHP at McGill include (1) the need for a dedicated senior faculty member to lead the program while promoting activities and initiatives, (2) the need for resources to begin new projects, and (3) a willingness to work with others to achieve common goals. Most medical schools already have faculty engaged in and students interested in global health activities. By bringing interested individuals together with a modest infusion of additional resources and creativity, it is possible to develop programs that provide exciting global health educational opportunities for the medical school community and beyond.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 0.003 |
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".