Corporate Crime and Punishment: The Politics of Negotiated Justice in Global Markets
Bibliographic record
Abstract
Over the past decade, many of the world’s biggest companies have found themselves embroiled in legal disputes over corruption, fraud, environmental damage, tax evasion, or sanction violations. Corporations including Volkswagen, BP, and Credit Suisse have paid record-breaking fines. Many critics of globalization and corporate impunity cheer this turn toward accountability. Others, however, question American dominance in legal battles that seem to impose domestic legal norms beyond national boundaries. In this book, Cornelia Woll examines the politics of American corporate criminal law’s extraterritorial reach. As governments abroad seek to respond to US law enforcement actions against their companies, they turn to flexible legal instruments that allow prosecutors to settle a case rather than bring it to court. With her analysis of the international and domestic politics of law enforcement targeting big business, Woll traces the rise of what she calls “negotiated corporate justice” in global markets. Woll charts the path to this shift through case studies of geopolitical tensions and accusations of “economic lawfare,” pitting the United States against the European Union, China, and Japan. She then examines the reactions to the new legal landscape, describing institutional changes in the common law countries of the United Kingdom and Canada and the civil law countries of France, Brazil, and Germany. Through an insightful interdisciplinary analysis of how the prosecution of corporate crime has evolved in the twenty-first century, Woll demonstrates the profound transformation of the relationship between states and private actors in world markets, showing that law is part of economic statecraft in the connected global economy.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.079 |
| Scholarly communication | 0.026 | 0.014 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".