EUROPEAN COMMISSION IN CETA NEGOTIATIONS: EXPLORING AGENT’S AUTONOMY
Bibliographic record
Abstract
As the world trade agenda began to cover “beyond the border” issues in the 1980s, the European Union (EU) gradually broadened the scope of its trade policy and adopted a more complex decision-making mechanism involving multiple actors. In the current EU institutional setting, the European Commission is empowered by the Council of the European Union to start a negotiation process with a trading partner. Once signed, an international trade agreement can only be concluded by the EU if it is approved by both the Council and the European Parliament. Although the Commission is responsible for executing the common commercial policy, its autonomy may be limited by the Council/member states and/or Parliament during trade negotiations. This article investigates the Commission’s autonomy in the EU-Canada Comprehensive Economic and Trade Agreement (CETA) negotiations from a principal-agent approach. It analyzes the conflictual dynamics of Council-Commission and Parliament-Commission principal-agent relations, focusing on investment and intellectual property negotiations. The article reveals that EU member states and the European Parliament restricted the European Commission’s autonomy and changed its initial position on these two controversial issues.
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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 | 0.021 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".