The wages of ethnic power: Socioeconomic status, group threat, and anti-immigrant attitudes in Western Europe
Bibliographic record
Abstract
Group threat theories explain anti-immigrant attitudes as emerging from threats to the perceived or actual power of one’s ethnic group. Studies also show that individual-level socioeconomic status (SES) is negatively correlated with attitudes toward immigrants, where SES is often conceptualized as an individual-level variable which relates to an individual’s experience of economic competition or general political orientation. Here we argue that the effect of SES is conditional on an individual’s ethnic group’s power. Using data from the European Social Survey and Ethnic Power Relations datasets, we examine how interactions between ethnic group power and individual SES shape attitudes toward immigrants across 16 Western European countries. We find that majority group members generally exhibit more anti-immigrant attitudes than members of minority groups. SES is negatively correlated with anti-immigrant attitudes, generally, but especially for majority group members, where lower-SES individuals have the most anti-immigrant attitudes. At the highest levels of SES there are almost zero differences in anti-immigrant attitudes between majority and minority group members. Our results highlight the need to look to how the “psychological wages” of ethnic group power are influenced by individual SES.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".