An Introduction: “Macroeconomic Policy Coordination and Domestic Politics: Policy Coordination in the EU from the European Semester to the Covid‐19 Crisis”*
Bibliographic record
Abstract
Abstract The Next Generation EU (NGEU) and the Recovery and Resilience Facility (RRF) encompassed the European Semester. To understand how and why this happened we apply different theoretical approaches so as to emphasize different aspects of this process. The contributions in this collection discuss three main questions: (1) Is the Semester successfully implemented in the domestic arena? (2) Do domestic institutions and stakeholders play a crucial role in the success (or lack thereof) of the Semester? (3) What lessons can we learn from past economic policy coordination for the challenges ahead? In answering these questions, one's lens needs to be focused at both the EU and the domestic levels. Various factors play a role: solidarity, mutual understanding, relations between the ‘South’ and the ‘North’, questions about democracy, the rule of law, the interaction between economic and social issues, and even the need to address the climate crisis (the Green Deal).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".