Enhancing Indigenous health research capacity in northern Ontario through distributed community engaged medical education at NOSM: A qualitative evaluation of the community engagement through research pilot program
Bibliographic record
Abstract
BACKGROUND: The Community Engagement Through Research (CETR) program matches Indigenous communities interested in exploring their own health research questions with NOSM learners seeking experience in health services research, supervised by faculty experienced in community-based participatory research. METHODS: Qualitative research was conducted using key informant interviews to examine outcomes of the matching of medical students with Indigenous distributed medical education (DME) communities in NOSM's distributed curriculum, in particular improvements for capacity for Indigenous health research in Northern Ontario. RESULTS: Interviews showed that community-centred research was appreciated by community, students and faculty and the social accountability aspect was acknowledged. Students and community members found meaning in the immediate applicability of the research to real community problems and felt inspired by it. The challenges that were identified were mainly related to time and resource constraints, including providing sufficient research training for learners, and the time period required for research ethics board approvals. CONCLUSIONS: The program successfully brought together communities interested in conducting their own health research, with medical students interested in learning about and conducting health research with Indigenous communities. It is therefore an example of successful community based participatory research supporting the social accountability mandate. Challenges are mainly administrative in nature. The program has the potential to be scalable and financially sustainable.
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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 | 0.250 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.072 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.015 |
| 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; both teacher heads agree on what is shown here.
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".