Bibliographic record
Abstract
Abstract The jurisprudence of the United States Supreme Court coupled with restrictive domestic arbitration legislation has created gaps in the enforcement of international arbitral subpoenas in the United States. These enforcement gaps restrict access to evidence by international arbitral tribunals seated in the United States and block such access entirely for foreign-seated international arbitral tribunals. These gaps also make the United States an outlier among other major international arbitration jurisdictions and conflicts with international arbitral practice. However, the recent decision of the United States Court of Appeals for the Ninth Circuit in Day v Orrick, Herrington & Sutcliffe is a first step toward filling these enforcement gaps. This article sets out the legislative framework governing the enforcement of international arbitral subpoenas in the United States, introduces the existing gaps in such enforcement, demonstrates how these gaps fly in the face of international arbitral practice and explains how the Ninth Circuit has now filled at least some of them. If followed by other federal courts, Day v Orrick may pave the way for the enforcement of subpoenas issued by international arbitral tribunals seated both within and outside the United States, and bring the United States back in line with international arbitral practice.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".