Multilevel Constitutional Review and EU External Treaty Making After Opinion 2/15
Bibliographic record
Abstract
Regional free trade agreements (FTAs), such as the EU-Singapore (EUSFTA) or the EU-Canada Comprehensive Economic and Trade Agreement (CETA), foresee judicial mechanisms for investor state dispute settlement (ISDS). The EU Treaties (TEU and TFEU) remain silent on the competence nature of external institution-building. It is no surprise therefore that ISDS causes inter-institutional disputes. Constitutionality reviews at national and EU level are challenged by ISDS institution-building. Examples are the German constitutional court’s 2016 decisions on CETA and its investment court system (ICS), and the Court of Justice of the European Union’s (CJEU) Opinion 2/15 on the EU-Singapore agreement. This article looks both at the national and supranational constitutional courts of a multilevel composite adjudication system of relevance to EU external relations, with a particular focus on ISDS. After some general considerations on Member State courts’ influences on EU external activities, the article compares the double-layered (competence and substance) review-approaches at both levels, to then analyse the recent application of these approaches to the Singapore agreement and CETA. The aim is to show that in external relations, as elsewhere, the EU depends on system-internal cooperation between its constitutional courts. As this is particularly important for institution-building, the article will also point to some legal uncertainties which these courts generate for ISDS.
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".