Outgroup Prejudice from an Evolutionary Perspective: Survey Evidence from Europe
Bibliographic record
Abstract
This study investigates the root causes of outgroup prejudice. The literature explains prejudice primarily as a result of the perception of threat or the lack of optimal intergroup contact. The literature also emphasizes that individuals who are prejudiced against one outgroup are more likely to be prejudiced against other outgroups as well. This study does not react to these established theories. Instead, it argues from an evolutionary social psychological perspective that the root cause of outgroup prejudice is an activated sense of distrust and caution. In ancestral environments, higher levels of distrust and caution helped humans better protect themselves and their offspring from outside dangers, especially that posed by other humans. Prejudice is thus a function of this general protective outlook rather than a function of the particular characteristics of outgroups. To test this hypothesis, the paper specifies six multilevel regression models and analyzes the factors that lead to prejudice against six salient minority groups: immigrants, Muslims, Jews, homosexuals, the Roma, and the people of different races. Data come primarily from the latest wave of the European Values Study, covering 43 European countries. In all six cases of outgroup prejudice, findings indicate a strong and consistent support for the proposed theoretical perspective.
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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 | 0.001 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".