Ethical research engagement with Indigenous communities
Bibliographic record
Abstract
INTRODUCTION: Canada's colonial policies and practices have led to barriers for Indigenous older adults' access to healthcare and research. As a result, there is a need for Indigenous-led research and culturally safe practices. Morning Star Lodge is developing a training module to assist AgingTech researchers on ethical, culturally safe ways to engage Indigenous communities. This includes exploring Indigenous health research, community-based partnerships, reciprocal learning, and cultural safety; this is presented through a case study on ethically engaged research. METHODS: Morning Star Lodge developed a research partnership agreement with File Hills Qu'Appelle Tribal Council and established a Community Research Advisory Committee representing the eleven First Nations within the Tribal Council. The work designing the culturally safe training module is in collaboration with the Community Research Advisory Committee. RESULTS: Building research partnerships and capacities has changed the way the eleven First Nation communities within File Hills Qu'Appelle Tribal Council view research. As a result, they now disseminate the knowledge within their own networks. CONCLUSIONS: Indigenous Peoples are resilient in ensuring their sustainability and have far more community engagement and direction. Developing culturally safe approaches to care for Indigenous communities leads to self-determined research. Culturally safe training modules can be applied to marginalized demographics.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".