Public consultation in the evaluation of animal research protocols
Bibliographic record
Abstract
In this study we invited public responses to five different research projects, using non-technical summaries intended for lay audiences. Our aim was to assess the potential for this type of public consultation in protocol review, and a secondary aim was to better understand what types of animal research people are willing to accept and why. US participants (n = 1521) were asked (via an online survey) “Do you support the use of these (insert species) for this research”, and responded using a seven-point scale (1 = “No”, 4 = “Neutral”, and 7 = “Yes”). Participants were asked to explain the reasons for their choice; open-ended text responses were subjected to thematic analysis. Most participants (89.7%) provided clear comments, showing the potential of an online forum to elicit feedback. Four themes were prevalent in participant reasoning regarding their support for the proposed research: 1) impact on animals, 2) impact on humans, 3) scientific merit, and 4) availability of alternatives. Participant support for the proposed research varied but on average was close to neutral (mean ± SD: 4.5 ± 2.19) suggesting some ambivalence to this animal use. The protocol describing Parkinson’s research (on monkeys) was least supported (3.9 ± 2.17) and the transplant research (on pigs) was most supported (4.9 ± 2.02). These results indicate that public participants are sensitive to specifics of a protocol. We conclude that an online forum can provide meaningful public input on proposed animal research, offering research institutions the opportunity for improved transparency and the chance to reduce the risk that they engage in studies that are out of step with community 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 | 0.788 | 0.745 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.006 | 0.022 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".