Immigration and the vote for the left: Measuring the effect of ethnic diversity on electoral outcomes at the district level
Bibliographic record
Abstract
In recent years, much has been written on the impact of immigration on Western political party systems and electoral landscapes. The vast majority of these works have sought to unravel the links between changes in a country’s ethnic composition and the rise and differential success of extreme and populist right-wing parties. Considerably less attention has been devoted to examining the effect of large migration rates on the fate of traditional parties, and in particular, on the vote of moderate left parties. Our article uses data from Madrid, Spain, where extreme right-wing or right-wing populist parties have not emerged as a significant electoral force and where immigration rates have grown considerably in the last decade. This provides an interesting context in which to understand how immigration may affect the distribution of the vote amongst traditional parties. The article analyzes whether the transfer of votes from the main moderate left to the main moderate right party during the period 1999—2008 is affected by neighborhood immigrant composition. Our results show that the increases in the votes to the main conservative party (or the decrease in the vote to the socialist party) can be partly explained by the changes in the ethnic composition of neighborhood.
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How this classification was reachedexpand
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 | 0.003 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".