Qualitative genomic research with Indigenous peoples: a scoping review of participatory practice
Bibliographic record
Abstract
INTRODUCTION: Indigenous peoples and perspectives are under-represented within genomic research. Qualitative methods can help redress this under-representation by informing the development of inclusive genomic resources aligned with Indigenous rights and interests. The difficult history of genomic research with Indigenous peoples requires that research be conducted responsibly and collaboratively. Research guidelines offer structuring principles, yet little guidance exists on how principles translate into practical, community-led methods. We identified the scope and nature of participatory practice described in published qualitative genomic research studies with Indigenous peoples. METHODS: We performed a search of PubMed, CINAHL, Embase, Scopus and the Bibliography of Indigenous Peoples in North America. Eligible studies reported qualitative methods investigating genomics-related topics with Indigenous populations in Canada, the USA, Australia or New Zealand. Abstracted participatory practices were defined through a literature review and mapped to a published ethical genomic research framework. RESULTS: We identified 17 articles. Published articles described a breadth of methods across a diversity of Indigenous peoples and settings. Reported practices frequently promoted Indigenous-partnered research regulation, community engagement and co-creation of research methods. The extent of participatory and community-led practice appeared to decrease as studies progressed. CONCLUSION: Applying non-prescriptive Indigenous genomic research guidelines to qualitative inquiry can be achieved through varied methodological approaches. Our findings affirm the adaptive nature of this process in real-world settings and identify opportunities for participatory practice and improved reporting across the research lifecycle. These findings and the breadth of characterised applied research practices are instructive for researchers seeking to develop much-needed qualitative genomic research partnerships.
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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 | 0.202 | 0.300 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.028 | 0.031 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier 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".