Culturally safe and ethical biomarker and genomic research with Indigenous peoples—a scoping review
Bibliographic record
Abstract
BACKGROUND: Indigenous peoples globally continue to be underrepresented in biomarker, genomic, and biobanking research. The aim of this study was to identify core components of culturally safe and ethical biomarker and genomic research with Indigenous peoples in Australia, Aotearoa/New Zealand, Canada and the USA. METHODS: A scoping review with a systematic search strategy was conducted utilising electronic databases MEDLINE, EMBASE, PsychINFO, CINAHL and Global Health. Key search terms included 'biomarkers' and 'genomics' research involving Indigenous peoples in relation to ethical and legal principles of respect, sovereignty, governance and existing policies. Original research studies published from the year 2000 to the 1st of August 2023 were reviewed in a systematic manner. Components of culturally safe and ethical research processes were identified and synthesised descriptively. The quality of included studies was assessed using an Aboriginal and Torres Strait Islander Quality Appraisal Tool through an Indigenous lens. RESULTS: Seven interrelated research components were identified from seventeen studies as core processes to enhance the cultural safety of biomarker and genomic research. These included building relationships and community engagement, learning, research coordination, logistics, consent, samples and biospecimens, biobank structures and protections and policy. The importance of ensuring self-determination, ownership and decision-making power is emphasised in processes to establish and conduct biomarker and genomic research with Indigenous peoples. CONCLUSIONS: Components that contribute to the cultural safety of biomarker and genomic research processes identified in this scoping review were assembled into a theoretical framework to guide research practice. Further evaluation is required by Indigenous peoples and communities to appropriate and adapt this framework for local use to promote the cultural safety of research processes and minimise barriers to Indigenous peoples' participation in biomarker and genomic research.
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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 | 0.051 | 0.140 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".