Interpersonal Disgust, Ideological Orientations, and Dehumanization as Predictors of Intergroup Attitudes
Bibliographic record
Abstract
Disgust is a basic emotion characterized by revulsion and rejection, yet it is relatively unexamined in the literature on prejudice. In the present investigation, interpersonal-disgust sensitivity (e.g., not wanting to wear clean used clothes or to sit on a warm seat vacated by a stranger) in particular predicted negative attitudes toward immigrants, foreigners, and socially deviant groups, even after controlling for concerns with contracting disease. The mechanisms underlying the link between interpersonal disgust and attitudes toward immigrants were explored using a path model. As predicted, the effect of interpersonal-disgust sensitivity on group attitudes was indirect, mediated by ideological orientations (social dominance orientation, right-wing authoritarianism) and dehumanizing perceptions of the out-group. The effects of social dominance orientation on group attitudes were both direct and indirect, via dehumanization. These results establish a link between disgust sensitivity and prejudice that is not accounted for by fear of infection, but rather is mediated by ideological orientations and dehumanizing group representations. Implications for understanding and reducing prejudice are discussed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".