Breaking barriers to ethical research: An analysis of the effectiveness of nonhuman animal research approval in Canada
Bibliographic record
Abstract
In Canada, all institutions that conduct publicly funded, animal-based research are expected to comply with the standards of the Canadian Council on Animal Care (CCAC). The CCAC promotes the use of animal alternatives, and uses the “3Rs” principles of Replacement, Reduction, and Refinement as a guiding ethical framework. To ensure these standards are strictly enforced, internal ethics committees at each institution are tasked with creating “Animal Use Protocol” (AUP) forms to be filled out by researchers and evaluated by the committees.In this paper, we assess AUP forms from Canada’s top research universities to identify the extent to which they conform to, or advance, the 3Rs framework. Our results show various deficiencies that call into question the quality of information elicited by these forms. To remedy this, we recommend that the CCAC assume responsibility for creating a standardized 3Rs section to be used on all AUP forms. In addition, proposal forms and experimental results for all research at CCAC-certified institutions should be digitized and uploaded into a national database. We argue that this would offer higher quality information for researchers at the experimental design stage, while strengthening the CCAC’s mandate to be accountable to the Canadian public.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Observational | high |
| gpt | Research integrityMetaresearch Domain: Methods · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Observational | low |
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 | 0.098 | 0.314 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.020 | 0.012 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".