Perceived Threat, Ethnic Minority Prejudice and the Riots in England
Bibliographic record
Abstract
Recent years have seen an increase in anti-immigrant and anti-ethnic minority sentiment in Britain and elsewhere. Yet while the scale of anti-immigrant hostility is well documented, its underlying drivers are less well understood. In this paper, we examine the role that different types of perceived threat - cultural, safety and economic - play in explaining prejudice towards three major minority groups: Muslims, Black British and East Europeans. Next, we explore how citizens’ immediate real world environment impacts on the salience of these perceived threats, and ultimately on ethnic prejudice, with a natural experiment in which the riots that occurred in major cities in England in August 2011 are used as a ‘situational trigger’. For this study we conducted two large nationally representative surveys before and after the riots. The results show that, in the aftermath of the riots, people were more likely to feel that their society’s security and culture were under threat, but did not feel more economically threatened. Moreover, because the rioting increased feelings of threat among a substantial portion of the British public, there was an increase in prejudice towards Black British and East Europeans communities.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".