Advancing Ethical Principles for Non-Invasive, Respectful Research with Nonhuman Animal Participants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Animal studies scholars are increasingly engaging with nonhuman animals firsthand to better understand their lifeworlds and interests. The current 3R framework is inadequate to guide respectful, non-invasive research relations that aim to encounter animals as meaningful participants and safeguard their well-being. This article responds to this gap by advancing ethical principles for research with animals guided by respect, justice, and reflexivity. It centers around three core principles: non-maleficence (including duties around vulnerability and confidentiality); beneficence (including duties around reciprocity and representation); and voluntary participation (involving mediated informed consent and ongoing embodied assent). We discuss three areas (inducements, privacy, and refusing research) that merit further consideration. The principles we advance serve as a starting point for further discussions as researchers across disciplines strive to conduct multispecies research that is guided by respect for otherness, geared to ensuring animals’ flourishing, and committed to a nonviolent ethic.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it