Pushed by markets, pulled by machines: Economic pressures and the backlash to the European Union
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
Global economic integration and automation technologies destabilise employment and threaten workers’ economic security, yet their combined political effects remain understudied. Using data from the ninth wave of the European Social Survey, this study examines how automation risks, measured by routine-task intensity and export-driven market pressure, foster Euroscepticism. This study finds that while routineness alone has a modest effect, its combination with trade exposure significantly amplifies negative sentiment towards the European Union, especially among individuals who perceive society as unfair and support redistribution. These economic vulnerabilities not only fuel Euroscepticism but also increase support for withdrawal from the European Union. The findings highlight the need for policies that mitigate technology-driven displacement, particularly for workers with high routine-task intensity in export-oriented sectors, with reinforcing fairness and redistributive mechanisms to sustain support for European integration.
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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 | 0.005 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 it