Eating with our eyes (closed): Effects of visually associating animals with meat on antivegan/vegetarian attitudes and meat consumption willingness
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
Negative attitudes toward vegetarians/vegans (i.e., veg*ns) are common, particularly among those who desire/like/consume meat more. In two studies, we replicated and extended past work, showing that visual reminders of meat’s animal origins (vs. images of meat alone) decreased meat consumption willingness via increased empathy for animals, distress about meat consumption, and disgust for meat. We also assessed how animal–meat reminders influence antiveg*n attitudes. In Study 1 ( N = 299) experimental animal–meat reminders (vs. meat-alone images) indirectly reduced negative attitudes toward veg*ns via increased empathy and distress (together, but not independently). The same manipulation in Study 2 ( N = 280) lowered antiveg*n attitudes through greater empathy and lowered veg*n threat through greater distress. Implications for promoting less antiveg*n attitudes are discussed.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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