Developing more inclusive approaches to animal research and patient involvement
Bibliographic record
Abstract
Doing scientific research with animals is a subject of intense societal debate, often involving polarized and public discussions with stakeholders and groups interested in animal research. Patients, given their medical conditions, have a high stake in biomedical research, including research involving animals. However, their perspectives are rarely heard in policy-related discussions on animal experiments. This essay discusses the positions and stakes of groups involved in public discourse and policy-relevant engagements. It further explores the legitimate interest of patients and the need for an all-inclusive approach to animal research policy. This subject is complex and democratic societies must address societal issues with an all-inclusive approach to reach policy decisions reflecting the interests of all stakeholders. The positions of groups-pro-animal research stakeholders and anti-animal-research advocates-with vested interests involved in animal research discourse considerably shape research policies. Animal research policies arguably affect patients. Through democratic ideals, inclusive approaches that are suitable for resolving science-driven societal issues, and initiatives currently guiding animal research policies, patients need to actively be involved in public discourses and policy-relevant decision-making processes in deciding the place of animal research in biomedical advancement as a society.
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
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".