The Open Method of Coordination and National Parliaments: Further Marginalization or New Opportunities?
Bibliographic record
Abstract
ABSTRACT Legislatures are central to national democracy. Yet, scholars examining the impact of the European Union (EU) on national parliaments (NPs) have concluded that integration undermines national legislatures. We call for a more nuanced and realistic analysis. We turn to the EU’s new forms of governance and, specifically, the Open Method of Coordination (OMC). Our analysis reveals a complex picture. On the one hand, by empowering governments through cooperative federalism, the OMC risks further marginalizing NPs. On the other hand, the OMC provides national legislators with opportunities that the traditional Community method of legislation cannot offer. First, the OMC gives national legislators access to an array of powerful, but also flexible, insights and tools for producing successful laws. Second, the OMC gives those legislators grounds for criticizing the policies of government officials. The empirical record suggests that NPs are already experiencing some of these contradictory effects. The conclusion calls for a reassessment of the position of NPs while stressing the need for stronger participation of NPs in EU politics. KEY WORDS Cooperative federalism; democratic representation; legislative insights;
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.028 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".