An Exception to Jesner: Preventing U.S. Corporations and Their Subsidiaries from Avoiding Liability for Harms Caused Abroad
Bibliographic record
Abstract
After the Supreme Court’s rulings in Jesner and Kiobel, the Alien Tort Statute includes a “presumption against extraterritorial application,” and no suits may be brought against foreign corporate defendants. These barriers limit the ability of victims of human rights violations to find justice. The courts or Congress should create an exception to the Alien Tort Statute for foreign corporate subsidiaries of domestic corporations. This exception will help improve American soft power and will hold human rights violators liable for their crimes. This Comment examines the policies of countries like France, England, Canada, and the Netherlands. The exception proposed by this Comment differs from the policies in these countries because it only asks the U.S. to create an exception for foreign corporations owned by American companies. The U.S. should not protect its corporations and grant them immunity when their subsidiaries engage in egregious human rights violations.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.017 | 0.011 |
| 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 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".