What’s the protocol? Canadian university research ethics boards and variations in implementing Tri-Council policy
Bibliographic record
Abstract
This article is concerned with the differences in REB policy and application processes across Canada as they impact multi-jurisdictional, higher education research projects that collect data at universities themselves. Despite the guiding principles of the Tri-Council Policy Statement 2 (TCPS2) there is significant variation among the practices of Research Ethics Boards (REBs) at Canada’s universities, particularly when they respond to requests from researchers outside their own institution. The data for this paper were gathered through a review of research ethics applications at 69 universities across Canada. The findings suggest REBs use a range of different application systems and require different revisions and types of oversight for researchers who are not employed at their institution. This paper recommends further harmonization between REBs across the country and national-level dialogue on TCPS2 interpretations.
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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 | 0.534 | 0.646 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.015 | 0.020 |
| Scholarly communication | 0.023 | 0.011 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.013 | 0.020 |
| Insufficient payload (model declined to judge) | 0.019 | 0.008 |
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".