Bibliographic record
Abstract
In this study, we examine which role the size of the immigrant population plays in explaining immigrant derogation within and between European regions. We draw upon group threat- and intergroup contact theory to consider the following question: does a larger size of immigrant population increase perceived group threat and thereby lead to greater immigrant derogation? Or does it increase intergroup contact and thereby ameliorate immigrant derogation? We test the empirical adequacy of these alternative suggestions using regionalized European Social Survey 2002 and official data which will be analyzed by means of multilevel structural equation modeling. Within regions, our results confirm that perceived group threat increases subsequent immigrant derogation. Likewise, intergroup contact reduces perceived group threat and thereby amends such derogation of immigrants. Between regions, our findings show that a larger size of the immigrant population increases both greater perceived group threat and intergroup contact. At the same time, the effects of perceived group threat and intergroup contact on immigrant derogation resemble those found within regions. In sum, these results lend evidence to the generalizability of both group threat- and contact effects. Implications of these findings for future research 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.004 |
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".