Shifting practise: recognizing Indigenous rights holders in research ethics review
Bibliographic record
Abstract
Purpose For many Indigenous nations globally, ethics is a conversation. The purpose of this paper is to share and mobilize knowledge to build relationships and capacities regarding the ethics review and approval of research with Indigenous peoples throughout Atlantic Canada. The authors share key principles that emerged for shifting practices that recognize Indigenous rights holders through ethical research review practice. Design/methodology/approach The NunatuKavut Inuit hosted and led a two-day gathering on March 2019 in Happy Valley-Goose Bay, Newfoundland and Labrador, to promote a regional dialogue on Indigenous Research Governance. It brought together Indigenous Nations within the Atlantic Region and invited guests from institutional ethics review boards and researchers in the region to address the principles-to-policy-to-practice gap as it relates to the research ethics review process. Called “Naalak”, an Inuktitut word that means “to listen and to pay close attention”, the gathering created a dynamic moment of respect and understanding of how to work better together and support one another in research with Indigenous peoples on Indigenous lands. Findings Through this process of dialogue and reflection, emergent principles and practices for “good” research ethics were collectively identified. Open dialogue between institutional ethics boards and Indigenous research review committees acknowledged past and current research practices from Indigenous peoples’ perspectives; supported and encouraged community-led research; articulated and exemplified Indigenous ownership and control of data; promoted and practiced ethical and responsible research with Indigenous peoples; and supported and emphasized rights based approaches within the current research regulatory system. Key principles emerged for shifting paradigms to honour Indigenous rights holders through ethical research practice, including: recognizing Indigenous peoples as rights holders with sovereignty over research; accepting collective responsibility for research in a “good” way; enlarging the sphere of ethical consideration to include the land; acknowledging that “The stories are ours” through Indigenous-led (or co-led) research; articulating relationships between Indigenous and Research Ethics Board (REB) approvals; addressing justice and proportionate review of Indigenous research; and, means of identifying the Indigenous governing authority for approving research. Research limitations/implications Future steps (including further research) include pursuing collective responsibilities towards empowering Indigenous communities to build their own consensus around research with/in their people and their lands. This entails pursuing further understanding of how to move forward in recognition and respect for Indigenous peoples as rights holders, and disrupting mainstream dialogue around Indigenous peoples as “stakeholders” in research. Practical implications The first step in moving forward in a way that embraces Indigenous principles is to deeply embed the respect of Indigenous peoples as rights holders across and within REBs. This shift in perspective changes our collective responsibilities in equitable ways, reflecting and respecting differing impetus and resources between the two parties: “equity” does imply “equality”. Several examples of practical changes to REB procedures and considerations are detailed. Social implications What the authors have discovered is that it is not just about academic or institutional REB decolonization: there are broad systematic issues at play. However, pursuing the collective responsibilities outlined in our paper should work towards empowering communities to build their own consensus around research with/in their people and their lands. Indigenous peoples are rights holders, and have governance over research, including the autonomy to make decisions about themselves, their future, and their past. Originality/value The value is in its guidance around how authentic partnerships can develop that promote equity with regard to community and researcher and community/researcher voice and power throughout the research lifecycle, including through research ethics reviews that respect Indigenous rights, world views and ways of knowing. It helps to show how both Indigenous and non-Indigenous institutions can collectively honour Indigenous rights holders through ethical research practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.046 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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, 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".