<i>Tetra Laval II</i>: the Coming of Age of the Judicial Review of Merger Decisions
Bibliographic record
Abstract
The article examines the European Court of Justice’s (``ECJ’’) ruling in Commission v. Tetra Laval regarding the scope of judicial review by the Court of First Instance (``CFI’’) in the merger control area and the standard of proof incumbent on the European Commission (the ``Commission’’) to support its merger decisions. First, the article describes how the ECJ ruling confirms that the CFI must ensure a thorough judicial review and provides precise guidance on the tests to be applied by it. The authors suggest such guidance applies to all types of merger decisions, including those adopted under the new EC Merger Regulation. Additionally, the article acknowledges a perceptible convergence of the courts of several Member States on the need for meaningful judicial review, in line with the Community Courts’ case law. Then, the article examines the ECJ’s reasoning as regards the standard of proof, and how the Commission must carry out its prospective analysis and substantiate its decisions. Based on the ruling, the authors conclude that the standard of proof should be the same for all types of mergers and for both clearance and prohibition decisions. Finally, on the question of whether the ruling also applies to antitrust decisions, the authors suggest that the need to establish convincingly the merits of an argument is more significant than the type of decision. The Commission will have to be more convincing in complex cases, particularly where it relies on novel theories of competitive harm.
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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 | 0.028 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.022 |
| Scholarly communication | 0.040 | 0.014 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.024 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 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".