"We don’t want immigrants because they don’t integrate ... and steal our jobs" : comparing economic and cultural influences on xenophobia in Canada, Australia and New Zealand
Bibliographic record
Abstract
Immigration has recently become a salient political issue in liberal democracies. Many political scientists have analyzed causes of emerging support for anti-immigrant parties, and the development of immigration control in Europe. Compared to the analysis of voting behavior and policy analysis, however, public opinion concerning immigration has not been fully examined in political science literature. Thus this study systematically the public opposition to immigration in opinion surveys by applying the theory of prejudice, theory of perceived threat to group position, social identity theory and contact theory. The analysis uses the election studies of Canada, Australia and New Zealand in varied years, which are merged with census data to examine contextual effects. The broad research question is who opposes immigration, why they oppose and under what conditions they are more likely to do so. The focus of the analysis in this thesis is on comparing the influences of economic and cultural factors. A brief review of the history of accepting immigrants in three countries reveals that both factors have significantly influenced the development of immigration policy. Although economic situation strongly influences the level of public’s opposition to immigration over time, the analysis of five election studies of three countries repeatedly shows that cultural concerns increase individuals’ probability of opposition more strongly than economic concerns. The analysis also finds that the local economic situation does not stably influence opposition to immigration, even if where immigrants are geographically concentrated. On the contrary, local economic situation increases the likelihood of opposition to immigration only where immigrants are not concentrated. Geographic concentration of immigrants does not have an interaction effect with economic concerns, but it magnifies the influence of one’s cultural concerns on opposition to immigration during the economic downturn. Accordingly, the examination of interactions effects reveals that even when contextual factors influence opposition to immigration, they interact with cultural concerns. Thus cultural concerns should be paid more attention for the politics of immigration for future research.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".