Exclusionary attitudes toward immigrants: Globalization and configurations of ascribed and achieved status across 14 European countries
Bibliographic record
Abstract
Research on immigration attitudes focuses on two dimensions of exclusionary preferences: those related to achieved characteristics and those related to ascribed characteristics. First, we expand this work by unpacking how individuals blend attitudes across these two dimensions. Applying latent profile analysis to a comprehensive set of exclusionary indicators from the European Social Survey in 2002 and 2014, we observe seven attitudinal configurations: exclusionary, moderate individualistic, individualistic, tolerant, religious, illiberal liberalism, and racial capitalism. Second, using multinomial logistic regression with country fixed effects, we explore how configurations relate to a period where European countries experienced overall economic de-globalization, but more intensified cultural globalization. Consistent with integrated threat theories, we find that exclusionary views were less common in countries that became economically de-globalized. Conversely, we find no effect of cultural globalization on the growth or decline of the exclusionary configuration. We conclude by considering the policy implications of these results on current immigration policy.
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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 | 0.002 | 0.003 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".