Toward reciprocity: host supervisor perspectives on international medical electives
Bibliographic record
Abstract
CONTEXT: An increasing number of medical students are engaging in international medical electives, the majority of which involve travel from northern, higher-income countries to southern, lower-income countries. Existing research has identified benefits to students participating in these experiences. However, reports on the impacts on host communities are largely absent from the literature. OBJECTIVES: The current study aims to identify host country perspectives on international medical electives. METHODS: Questionnaires were delivered to a convenience sample of supervisors hosting international elective students (n = 39) from a Canadian medical school. Responses represented 22 countries. Conventional content analysis of the qualitative data was used to identify themes in host supervisor perspectives on the impact of international medical electives. RESULTS: Host country supervisors identified that in addition to the benefits realised by the elective students, supervisors and their institutions also benefited from hosting Canadian students. Although some host supervisors denied the occurrence of any harm, others expressed concern that international elective students may negatively impact the local community in terms of resource use and patient care. Host country supervisors also identified potential harms to travelling students including health risks and emotional distress. Ideas for improving international electives were identified and were largely centred around increasing the bidirectional flow of students by establishing formal partnerships between institutions. CONCLUSIONS: This research provides important insights into the impacts of international medical student electives from the perspective of host country supervisors. This research may be a starting point for further research and the establishment of meaningful partnerships that incorporate the self-identified needs of receiving institutions, especially those in lower-income settings.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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".