McMaster University Internal Medicine International Health Elective: A Survey-Based Study to Understand Achievements and Lessons Learned
Bibliographic record
Abstract
Summary The McMaster Internal Medicine International Health Elective (IHE) has been placing senior medical residents (PGY-3) in an elective setting in a teaching hospital in Kampala, Uganda, for the past 7 years. This article discusses a study in which the authors electronically mailed a survey to alumni of this elective to evaluate important aspects of program participation from the residents’ point of view. The factors most commonly cited as being important in the decision to apply to the McMaster IHE were to gain experience practising medicine in a resource-limited setting and to gain exposure to diseases and conditions not commonly encountered in Canada. Most residents (61.5%) planned to have some involvement in global health prior to their elective, and 100% felt the elective experience made them more likely to take part in global health activities in the future. IHEs offer a unique opportunity for residents to explore global health. Residents participating in this survey found the McMaster Internal Medicine IHE to be a successful endeavour.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".