Survey of Canadian Animal-Based Researchers' Views on the Three Rs: Replacement, Reduction and Refinement
Bibliographic record
Abstract
The 'Three Rs' tenet (replacement, reduction, refinement) is a widely accepted cornerstone of Canadian and international policies on animal-based science. The Canadian Council on Animal Care (CCAC) initiated this web-based survey to obtain greater understanding of 'principal investigators' and 'other researchers' (i.e. graduate students, post-doctoral researchers etc.) views on the Three Rs, and to identify obstacles and opportunities for continued implementation of the Three Rs in Canada. Responses from 414 participants indicate that researchers currently do not view the goal of replacement as achievable. Researchers prefer to use enough animals to ensure quality data is obtained rather than using the minimum and potentially waste those animals if a problem occurs during the study. Many feel that they already reduce animal numbers as much as possible and have concerns that further reduction may compromise research. Most participants were ambivalent about re-use, but expressed concern that the practice could compromise experimental outcomes. In considering refinement, many researchers feel there are situations where animals should not receive pain relieving drugs because it may compromise scientific outcomes, although there was strong support for the Three Rs strategy of conducting animal welfare-related pilot studies, which were viewed as useful for both animal welfare and experimental design. Participants were not opposed to being offered "assistance" to implement the Three Rs, so long as the input is provided in a collegial manner, and from individuals who are perceived as experts. It may be useful for animal use policymakers to consider what steps are needed to make replacement a more feasible goal. In addition, initiatives that offer researchers greater practical and logistical support with Three Rs implementation may be useful. Encouragement and financial support for Three Rs initiatives may result in valuable contributions to Three Rs knowledge and improve welfare for animals used in science.
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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 | 0.062 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| 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, 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".