Bibliographic record
Abstract
Horizontal agreements between competitors concerning price fixing, quotas, distribution and/or supply market share – cartels – represent the most severe form\nof competition law infringement. Why are these agreements subject to the highest fines and, in some countries (USA, Canada, Mexico, UK), subject to both fines as well as imprisonment? What are the economic grounds for such severe punishment?\nHow important is an economic analysis for the results of anti-cartel proceedings\nconsidering that they are prohibited per se, that is, absolutely and unconditionally?\nDoes growing market concentration and resulting transparency increase the\nsignificance of the economic approach to the evaluation of market effects of the\nbehaviour of business? Which methods make it possible to differentiate cartels from\ncompetition in oligopolistic markets including economic and econometric analyses?\nThis paper will present an answer to the aforementioned questions on the basis of\nliterature studies, an analysis of Polish case law between 2000–2009 as well as the\nauthor’s extensive experience in the field of antitrust consultancy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".