Enacting Research Ethics in Partnerships with Indigenous Communities in Canada: “Do it in a Good Way”
Bibliographic record
Abstract
Two studies conducted through community-campus partnerships demonstrated emerging frameworks for ethical conduct of research involving Indigenous peoples in Canada. Both projects involved multiple Indigenous community partners whose interests in promoting children's development and fathers' involvement motivated the projects. The Indigenous projects were conceived within a broader social agenda of restorative justice and self-determination of Indigenous peoples in Canada following centuries of colonial government interventions. Guiding principles included community relevance, community participation, mutual capacity building, and benefit to Indigenous communities. Memoranda of Understanding negotiated with each community partner specified the roles of community and university partners and research team members in each phase of the research. Testimonials obtained from community representatives before and after the research projects indicated the success of the projects in yielding benefits to the communities in the form of substantive knowledge and strengthened capacities to engage in collaborative research through community-campus partnerships. The larger collaborative research projects in which these two Indigenous projects were embedded created challenges and opportunities due to varying recognition within these networks of the primacy of relationships as a foundation for research and the indeterminacy of outcomes when ownership of data and control over dissemination is in the hands of community partners.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Qualitative | low |
| gpt | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Qualitative | low |
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 | 0.063 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.063 | 0.042 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".