Community engagement in global health education supports equity and advances local priorities: an eight year Ecuador-Canada partnership
Bibliographic record
Abstract
BACKGROUND: Global health education initiatives inconsistently balance trainee growth and benefits to host communities. This report describes a global health elective for medical trainees that focuses on community engagement and participatory research to provide mutually beneficial outcomes for the communities and trainees. METHODS: An eight-year university-community partnership, the Chilcapamba to Montreal Global Health Elective is a two-month shared decision-making research and clinical observership experience in rural Ecuador for medical trainees at McGill University, Canada. Research topics are set by matching community-identified priorities with skillsets and interests of trainees, taking into consideration local potential impact. RESULTS: Community outcomes included development of a Community Health Worker program, new collaborations with local organizations, community identification of health priorities, and generation of health improvement recommendations. Collaborative academic outputs included multiple bursary awards, conference presentations and published manuscripts. CONCLUSION: This medical global health elective engages communities using participatory research to prioritise socially responsible and locally beneficial outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".