Research Ethics Review and Aboriginal Community Values: Can the Two Be Reconciled?
Bibliographic record
Abstract
CONTEMPORARY RESEARCH ETHICS REVIEW COMMITTEES (RECs) are heavily influenced by the established academic or health care institutional frameworks in which they operate, sharing a cultural, methodological and ethical perspective on the conduct of research involving humans. The principle of autonomous choice carries great weight in what is a highly individualistic decision-making process in medical practice and research. This assumes that the best protection lies in the ability of patients or research participants to make competent, voluntary, informed choices, evaluating the risks and benefits from a personal perspective. Over the past two decades, North American and international indigenous researchers, policy makers and communities have identified key issues of relevance to them, but ignored by most institutional or university-based RECs. They critique the current research review structure, and propose changes on a variety of levels in an attempt to develop more community sensitive research ethics review processes. In doing so, they have emphasized recognition of collective rights including community consent. Critics see alternative policy guidelines and community-based review bodies as challenging the current system of ethics review. Some view them as reflecting a fundamental difference in values. In this paper, we explore these developments in the context of the political, legal and ethical frameworks that have informed REC review. We examine the process and content of these frameworks and ask how this contrasts with emerging Aboriginal proposals for community-based research ethics review. We follow this with recommendations on how current REC review models might accommodate the requirements of both communities and RECs.
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 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 | 0.410 | 0.418 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.015 | 0.150 |
| Scholarly communication | 0.048 | 0.072 |
| Open science | 0.009 | 0.027 |
| Research integrity | 0.031 | 0.038 |
| 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".