On Banks, Courts and International Law:A Critical Analysis of the Draft International Agreement on the Functioning of the Single Resolution Fund
Bibliographic record
Abstract
In December 2013 the ECOFIN Council has given its green light to the adoption of the second pillar of the so-called Banking Union: a Single Resolution Mechanism to wind down failing banks in the Euro-zone, and thus break the cycle between banks and sovereigns in the EU. Besides a regulation, to be adopted in co-decision procedure with the Parliament, the Council has however endorsed a plan to adopt an international agreement on the functioning of the Single Resolution Fund (SRF). The paper critically analyses the choice to resort to international law to establish the SRF. As the paper maintains, the use of an intergovernmental agreement in this case is not necessary from a legal point of view. In fact, the use of international law in this case rests on flawed legal argument, namely that EU regulations cannot impose financial obligations on the states. Moreover, as the paper explains, the use of international law generates bad policy outcomes. Resort to international law to establish the SRF opens the door for national courts’ review of the agreement – a prospect which contrasts with the constitutional logic of leaving decision of economic questions in the political process. In light of these weaknesses, the paper concludes that the European Parliament should endeavor to block the intergovernmental avenue and bring back the regulation of the SRF within the framework of EU law.
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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 | 0.037 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.016 | 0.042 |
| Scholarly communication | 0.034 | 0.022 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.023 | 0.019 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".