Bibliographic record
Abstract
Neelie Kroes, Enforcement of Prohibition of Cartels in Europe Joseph E. Harrington, Jr., Behavioral Screening and the Detection of Cartels Patrick Rey, On the Use of Economic Analysis in Cartel Detection Paul Grout, Predicting Cartels Richard Whish, Oligopoly Theory and Economic Evidence Rafael Allendesalazar Corcho, Oligopolies, Conscious Parallelism and Concertation Calvin S. Goldman QC, The Investigative Powers of the Canadian Competition Bureau: Domestic and International Dimensions Ian S. Forrester, QC, Searches Beneath the Cherry Tree in the Garden: European Thoughts on How to Enchance the Task of Uncovering and Thereby Deterring Olivier Guersent, The EU Model of Administrative Enforcement Against Global Cartels: Evolving to Meet Challenges Philip Collins, Some Background Notes on the Investigative Powers of the Competition Authorities Thomas O. Barnett, Seven Steps to Better Cartel Enforcement Public Enforcement (Administrative and Criminal) James Venit, Modernization and Enforcement - The Need for Convergence: On Procedure and Substance Nadia Calvino, Public Enforcement in the EU: Deterrent Effect and Proportionality of Fines Massimo Motta On the Effect of EU Cartel Investigations and Fines on the Infringing Firms' Market Value Stephen Calkins, Coming to Praise Criminal Antitrust Enforcement Wouter P. J. Wils, Is Criminalization of EU Competition Law the Answer? Denis Waelbroeck, The Commission's Green Paper on Private Enforcement: 'Americanization' of EC Competition Law Enforcement? Donncadh Woods, The Commission Green Paper on Damages Actions for Breach of the EC Antitrust Rules Jon Lawrence, Seeking the Perfect Balance: Some Reflections on the Commission Green Paper on Damages Actions for Breach of the EC Antitrust Rules Mario Siragusa, A Reflection on Some Private Antitrust Enforcement Issues Donald C. Klawiter, US Corporate Leniency After the Blockbuster Cartels: Are We Entering a New Era? Jochen Burrichter, Reflections on the Implementation of a Plea Bargaining/Direct Settlement-System in EC Competition Law John Ratliff, Plea Bargaining in EC Anti-Cartel Enforcement - A System Change? Julian M. Joshua, That Uncertain Feeling: The Commission's 2002 Leniency Notice Margaret Bloom, Despite Its Great Success, the EC Leniency Program Faces Great Challenges William E. Kovacic, Bounties as Inducements to Identify Cartels Nicholas Forwood, Effective Enforcement and Legal Protection - Friends or Enemies? Peter Roth, Ensuring that Effectiveness of Enforcement Does Not Prejudice Legal Protection. Rights of Defence. Fundamental Rights Concerns Christopher Harding, Effectiveness of Enforcement and Legal Protection
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".