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Record W4327546579 · doi:10.1093/arbint/aiad008

Enforcing international arbitral subpoenas in the United States

2023· article· en· W4327546579 on OpenAlexaff
Tamar Meshel

Bibliographic record

VenueArbitration International · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEnforcementNinthArbitrationLawSupreme courtInternational arbitrationPolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.026
GPT teacher head0.262
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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