Social Failures of EU Enlargement: A Case of Workers Voting with their Feet
Bibliographic record
Abstract
Is the EU enlargement the success EU institutions proclaim? Based on fifteen years of fieldwork research across Central and Eastern Europe and on migrants in the UK and Germany, this book provides a less glittering answer. The EU has betrayed hopes of social cohesion: social regulations have been forgotten, multinationals use threats of relocations, and workers, left without institutional channels to voice their concerns, have reacted by leaving their countries en masse. Yet migration, for many, increases social vulnerability. Drawing on Hirschman's concepts of Exit and Voice, the book traces the origins of such failures in the management of EU enlargement as a pure economic and market-creating exercise, neglecting the inherently political nature of labour relations. The reinforcement of market mechanisms without political counterbalances has resulted in an increase in opportunistic exit behaviour by both employers and employees, and thereby in a worsening quality of democracy, at workplace, national and European levels. As a result of this process, the EU has become more similar to the North American Free Trade Agreement between USA, Canada and Mexico, where social rights are marginalized and economic integration does not translate into better development. --
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.014 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".