Jurisdictional Countermeasures Versus Extraterritoriality in International Law
Bibliographic record
Abstract
Sovereignty is the reason why States seek to apply their jurisdictions. All States like to extend their jurisdictions as far as they can, so some of them have adopted extraterritorial policies in exercising their jurisdictions. In this manner the United States has approved several extraterritorial Laws in respect of competition law and sanctions, causing some coercion to non-target states. In response to this long-arm jurisdiction by the U.S., some countries, such as the U.K., Canada, Australia, Mexico etc., as well as the E.U., took actions of their own in order to nullify these extraterritorial laws. These measures, which are mostly applied to the jurisdictional field, could be described as jurisdictional countermeasures. They can be divided into prescriptive, adjudicative and executive measures, which include blocking statutes, claw-back statutes, non-recognition, procedural restrictions, non-execution and retaliatory measures. Not all of these measures are prohibited by international law and some can be viewed as a just retorsion against that State. However, where the application of these measures is prohibited by international law – in cases such as the non-recognition of foreign judgments and other jurisdictional regulations in international treaties like mutual judicial assistance agreements – they are countermeasures. If these actions are in response to an illegal extraterritorial law, they should comply with the conditions for countermeasures as cited in the Draft Articles on Responsibility of States for Internationally Wrongful Acts 2001 as approved by the International Law Commission.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.048 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".