European competition law annual 2011 : integrating public and private enforcement of competition law : implications for courts and agencies
Bibliographic record
Abstract
This volume contains papers presented at the 16th Annual EU Competition Law and Policy Workshop, held at the European University Institute on 17-18 June 2011. This edition of the Workshop examined the emerging and increasingly important use of private rights of action before national courts, and the prospects for legislation and soft law initiatives at the level of the EU. The book has been updated and reflects the European Commission's private enforcement package of June 2013. Furthermore, the experiences of various national jurisdictions are discussed, both within Europe and in the US and Canada. As a whole, the volume explores how public and private enforcement might function harmoniously, as an 'integrated' system, to promote the public interest while ensuring that individual rights created in this field by the EU competition rules are vindicated. The contributors have, however, devoted significant analysis to the tensions between those two modes of enforcement.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".