Measuring Economic Reform Recommendations under the European Semester: ‘One Size Fits All’ or Tailoring to Member States?
Bibliographic record
Abstract
In 2010 the European Semester was created to better coordinate fiscal and economic policies within Europe’s Economic and Monetary Union. The Semester aims to tackle economic imbalances by giving European Union (EU) member states country-specific recommendations (CSRs) regarding their public budgets as well as their wider economic and social policies with a view to enabling better policy coordination among Euro Area member states. In this article we develop a method to assess the way in which the CSRs have been addressing coordination and offer a systematic analysis of the way they have been formulated. We offer a way to code CSRs as well as one to analyse progress evaluations. Furthermore, we seek to use our results to address one of the reoccurring questions in the literature: whether the EU is pursuing a ‘one size fits all’ approach to economic policy making in the Euro Area? The findings indicate that different types of market economies and welfare states – different ‘varieties of capitalism’ – among the Euro Area members obtain different recommendations regarding different policy areas
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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 | 0.023 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".