Animating the concept of “ethical space”: The Labrador Aboriginal Health Research Committee Ethics Workshop
Bibliographic record
Abstract
This paper reports on an innovative process by which the Inuit and First Nations communities of Newfoundland and Labrador confronted and challenged the policies and procedures of the provincial research ethics system. We describe the ways in which these communities engaged with health and university research review administrators to exchange information, identify challenges with existing processes, and outline a strategy for movement forward. We highlight the innovative structure of the process, and show how that resulted in immediate and ongoing community-led reforms to the provincial research ethics boards. Key to the success of the workshop was the fact that diverse stakeholders—community members, community research review administrators, research ethics board administrators, and health board research administrators—came together in an ethical space and worked together to critically interrogate the bureaucratic structure of the government, health, and university-based ethics review processes in the province. Recommendations arising from this process led to changes in the governance of health research involving the province’s Indigenous communities.
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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 | 0.223 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.050 | 0.058 |
| Scholarly communication | 0.022 | 0.006 |
| Open science | 0.006 | 0.020 |
| Research integrity | 0.010 | 0.026 |
| Insufficient payload (model declined to judge) | 0.003 | 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".