Damages for Schneider Electric: Setting the Standards for Community's Non-Contractual Liability
Bibliographic record
Abstract
The CFI Schneider judgement on damages represents an important milestone in the development of the EC competition law as it was the first time that damages have been awarded by the Court in a merger case. However, its impact on future damage claims is far from clear. First, it should be noted that incompatibility decisions of the Commission are extremely rare, as is their annulment by the Community courts. In this respect the Schneider case stands in line with the famous Airtours, General Electric and Tetra Laval mergers. Secondly, Schneider has already consummated the transaction at the time when the incompatibility decision was adopted which, as a result, had contributed to its damages sustained.
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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 | 0.023 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.018 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".