When Closing the Human–Animal Divide Expands Moral Concern
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
Humans and animals share many similarities. Across three studies, the authors demonstrate that the framing of these similarities has significant consequences for people’s moral concern for others. Comparing animals to humans expands moral concern and reduces speciesism; however, comparing humans to animals does not appear to produce these same effects. The authors find these differences when focusing on natural tendencies to frame human–animal similarities (Study 1) and following experimental induction of framings (Studies 2 and 3). In Study 3, the authors extend their focus from other animals to marginalized human outgroups, demonstrating that human–animal similarity framing also has consequences for the extension of moral concern to other humans. The authors explain these findings by reference to previous work examining the effects of framing on judgments of similarity and self-other comparisons and discuss them in relation to the promotion of animal welfare and the expansion of moral concern.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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