Bibliographic record
Abstract
Abstract What mechanisms do the EU Treaties provide to resolve conflicts between the EU institutions and the Member States in the conduct of their respective foreign relations? And how do those mechanisms compare to the ones in Canada, Belgium, and the US discussed in the previous chapter? Chapter 5 explains how the EU Treaties provide for two formal, judicial conflict resolution mechanisms: the ERTA pre-emption doctrine and the duty of sincere cooperation. In addition, secondary EU legislation endows the European Commission with a number of sector-specific political conflict resolution mechanisms. Compared to the other federal unions explored in this book, the conflict resolution mechanisms in the EU Treaties are primarily judicial and formal in nature. The Court of Justice plays a central role in resolving conflicts between the EU institutions and the Member States. The judicial and formal nature of conflict resolution mechanisms in the EU distinguishes the EU from both Belgium and Canada, which both rely on political mechanisms—in the former they are more formal; in the latter informal. And it highlights a commonality with the US. There, too, conflicts are resolved through the application of constitutional principles enforced by the (federal) courts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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 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".