Standards of Proof and Standards of Judicial Review in European Commission Merger Law
Bibliographic record
Abstract
This Article considers, in light of the judgment in Tetra Laval ECJ, what standard the Commission's decisions in the field of merger control must satisfy if they are to withstand judicial scrutiny, and whether the Commission's concerns that the standard has been raised are justified. We also consider how the Courts' review of Commission decisions has evolved, what the standard of such judicial review now is, and what margin of appreciation is left to the Commission. Along the way, some observations are made as to how the position could be clarified further so as to ensure a satisfactory competition law regime that inspires confidence and promotes legal certainty.
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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 | 0.282 | 0.480 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.011 | 0.060 |
| Scholarly communication | 0.038 | 0.023 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.040 | 0.022 |
| Insufficient payload (model declined to judge) | 0.003 | 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".