The “Refugee Crisis,” Immigration Attitudes, and Euroscepticism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Between 2015 and 2017, the European Union (EU) was confronted with a major crisis in its history, the so-called “European refugee crisis.” Since the multifaceted crisis has provoked many different responses, it is also likely to have influenced individuals’ assessments of immigrants and European integration. Using data from three waves of the European Social Survey (ESS) — the wave before the crisis in 2012, the wave at the beginning of the crisis in 2014, and the wave right after the (perceived) height of the crisis in 2016 — we test the degree to which the European refugee crisis increased Europeans’ anti-immigrant sentiment and Euroscepticism, as well as the influence of Europeans’ anti-immigrant attitudes on their level of Euroscepticism. As suggested by prior research, our results indicate that there is indeed a consistent and solid relationship between more critical attitudes toward immigrants and increased Euroscepticism. Surprisingly, however, we find that the crisis increased neither anti-immigrant sentiments nor critical attitudes toward the EU and did not reinforce the link between rejection of immigrants and rejection of the EU. These findings imply that even under a strong external shock, fundamental political attitudes remain constant.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it