Interpersonal Disgust, Ideological Orientations, and Dehumanization as Predictors of Intergroup Attitudes
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
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| 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