Political Mobilisation, Ethnic Diversity and Social Cohesion: The Conditional Effect of Political Parties
Why this work is in the frame
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Bibliographic record
Abstract
Recent research on the consequences of ethnic diversity for social cohesion indicates that the effects of diversity are not necessarily universal. In this article we hypothesise that the rhetoric of political parties conditions whether diversity negatively affects generalised trust. Political campaigns might highlight the salience of cultural diversity issues in their discourse or, moreover, use a divisive rhetoric of ‘nationalistic’ positions. Thus political mobilisation might heighten the perceived conflict between those who are native born and immigrants, especially in diverse societies. In order to test this argument, we investigate the influence of political rhetoric framed on cultural diversity issues, that is, nationalism and multiculturalism — obtained from the Comparative Manifestos Project– on generalised trust in 21 European democracies. We find that the negative impact of ethnic diversity on trust is particularly strong when these issues are mobilised by political parties. It does not, however, matter whether these issues are presented in a positive or negative light.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it