Social and economic ideologies differentially predict prejudice across the political spectrum, but social issues are most divisive.
Bibliographic record
Abstract
Liberals and conservatives both express prejudice toward ideologically dissimilar others (Brandt et al., 2014). Previous work on ideological prejudice did not take advantage of evidence showing that ideology is multidimensional, with social and economic ideologies representing related but separable belief systems. In 5 studies (total N = 4912), we test 3 competing hypotheses of a multidimensional account of ideological prejudice. The dimension-specific symmetry hypothesis predicts that social and economic ideologies differentially predict prejudice against targets who are perceived to vary on the social and economic political dimensions, respectively. The social primacy hypothesis predicts that such ideological worldview conflict is experienced more strongly along the social than economic dimension. The social-specific asymmetry hypothesis predicts that social conservatives will be more prejudiced than social liberals, with no specific hypotheses for the economic dimension. Using multiple target groups, multiple prejudice measures (e.g., global evaluations, behavior), and multiple social and economic ideology measures (self-placement, issue positions), we found relatively consistent support for the dimension-specific symmetry and social primacy hypotheses, and no support for the social-specific asymmetry hypothesis. These results suggest that worldview conflict and negative intergroup attitudes and behaviors are dimension-specific, but that the social dimension appears to inspire more political conflict than the economic dimension. (PsycINFO Database Record
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".