Why the right resists veg(etari)anism: Ideological commitment to consuming animal products
Bibliographic record
Abstract
Right-wing adherents — those higher in social dominance orientation (SDO) or right-wing authoritarianism (RWA) — tend to show stronger commitment to consuming meat, partly due to beliefs in human superiority over animals and resistance to the perceived threat that veg(etari)anism poses to traditional food norms. In two large-scale surveys ( N s = 870 and 1142), we investigated whether these ideological dispositions also predict commitment to dairy, eggs, and fish, not just meat, and more favourable evaluations of animal-based (vs. plant-based) alternatives. The findings demonstrated that the effects of right-wing ideological dispositions (SDO and RWA) persist across different types of animal products and dietary groups, including omnivores, flexitarians, pescatarians, and vegetarians. Perceived veg(etari)anism threat significantly mediated the associations for both SDO and RWA, while human supremacy beliefs also mediated the associations for SDO. These results suggest that animal product consumption and resistance to plant-based alternatives are shaped by ideological worldviews rooted in group-based dominance and cultural traditionalism. Efforts to reduce animal product consumption may need to engage with these underlying ideological narratives. • Right-wing ideology predicts stronger meat commitment. • But does meat hold a unique ideological role in dietary behaviour?. • Two large-scale studies show these effects for dairy, egg, and fish, not just meat. • Human supremacy beliefs and veg(etari)anism threat explain the associations. • Commitment to animal products reflects dominance and tradition-based ideologies.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".