Bibliographic record
Abstract
International cartelists face investigations and possible fines in a score of national and supranational jurisidictions, but the three with the most consistent legal responses to global cartels are the United States, Canada, and the European Union. This paper examines the antitrust fines and private penalties imposed on the participants of 167 international cartels discovered during 1990-2003. While more than U.S. $10billion in penalties has been imposed, it is doubtful that such monetary sanctions can deter modern international cartels. The apparently large size of government fines is distorted by one overwhelming case. Moreover, deterrence is frustrated by the failure of compensatory private suits to take hold outside of North America and the near absence of fines in most Asian jurisdictions. Without significant increases in cartel detection, in the levels of expected fines or civil settlements, or expansion of the standing of buyers to seek compensation, international price fixing will remain rational business conduct.
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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 | 0.000 | 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 | 0.000 |
| 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".