Bringing Ethics Review Home to Cowichan: Indigenizing Ethics Review in British Columbia, Canada
Bibliographic record
Abstract
Cowichan Tribes’ territory, located in the Cowichan Valley on Vancouver Island, British Columbia, Canada, is experiencing an alarmingly high rate of preterm births compared to the national average of Indigenous Peoples in Canada. In response, and in partnership with the First Nations Health Authority (FNHA), Cowichan Tribes is in the first year of a 3-year study to investigate causes. Cowichan Tribes’ Elders and community members are guiding the study to ensure it follows Cowichan Tribes’ research processes and to support self- determination in research. Furthermore, as a way to enhance reconciliation, Elders and community members guided an on-site ethics review on Cowichan Tribes territory. This article outlines the collaborative, in-person research ethics review process that Cowichan Tribes, Island Health, and FNHA completed on August 21, 2019. The purpose of this article is to provide suggestions other First Nations could use when conducting a research ethics review, and to explain how this process aligns with the principles of ownership, control, access, and possession (OCAP®), the United Nations Declaration on the Rights of Indigenous Peoples, the Truth and Reconciliation Commission of Canada, and above all, the Cowichan snuw’uy’ulh (teachings from Elders).
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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 | 0.149 | 0.240 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.052 | 0.036 |
| Scholarly communication | 0.023 | 0.006 |
| Open science | 0.007 | 0.015 |
| Research integrity | 0.009 | 0.018 |
| 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; 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".