JUDICIAL SCRUTINY OF MERGER DECISIONS IN THE EU, UK AND GERMANY
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The appropriate role of the courts in controlling the discretion of merger authorities has become one of the key issues in European merger law and policy in recent years. This article investigates judicial review of merger decisions, taking a comparative approach by examining cases from the EU, UK and Germany. We observe an apparent increase in the willingness of the EU and UK courts to scrutinize merger decisions, and a long-standing tradition of close scrutiny in Germany. In respect of the EU and UK, we consider agency theory offers a convincing explanation—that increased scrutiny is explained by the need to enhance the credibility of merger policy. In Germany, the constitutional basis of judicial review differs significantly, and the relatively close scrutiny exercised by the court is better explained by the very different constitutional context.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it