The European Semester in the North and in the South: Domestic Politics and the Salience of EU‐Induced Wage Reform in Different Growth Models*
Bibliographic record
Abstract
Abstract Macro‐economic policy coordination remains a challenge in the EU. The European Semester was designed to help facilitate more coordination. In the area of wage policies, it encourages Germany and the Netherlands to support stronger wage growth, while Italy and Portugal have been told to exercise wage restraint. This paper analyses how domestic interest group politics influence how EU recommendations are received. Reflecting on the different growth models that underpin these four countries, we find that country‐specific recommendations meet country‐specific obstacles – independent of whether recommendations aim at increasing or reducing wages. Specifically, we observe that domestic actors successfully mobilize against EU recommendations that go against the interests of their constituencies, but are less effective in mobilizing for recommendations aligning with their interests. Hence, we submit that high salience of EU influence poses an obstacle for EU‐induced reform in the South while low salience limits EU influence in the North.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".