Factors Affecting People's Acceptance of the Use of Zebrafish and Mice in Research
Bibliographic record
Abstract
The species of laboratory animal used is known to influence people's willingness to support animal-based research. An online experiment was used to test people's willingness to accept the use of zebrafish or mice, two of the most commonly used species, in research involving either induced mutation (specifically, ethyl-N-nitrosourea [ENU] mutagenesis) or genetic modification, with and without regulatory oversight. Participants who were willing to support research on zebrafish (31.9%) were also willing to support the same research on mice. The participants expressed low levels of support for research involving ENU mutagenesis of zebrafish in both unregulated (30.7%) and regulated (38.5%) research programmes. A reason for the rejection of ENU mutagenesis was the perception that the procedure is painful. Some participants expressed a preference for the use of genetically-modified (GM) animal models over ENU mutagenesis, based on the belief that the former involves less pain and improves both the accuracy and efficiency of the animal models. Better informing the public about scientific practice, and scientists about public attitudes, may help reduce the disconnect between scientific practice and societal values.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".