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Record W4384935478 · doi:10.1093/arbint/aiad042

Jurisdictional overlap between domestic courts and investment arbitration: an occasion for judicial dialogue

2023· article· en· W4384935478 on OpenAlexaff
Mees Brenninkmeijer

Bibliographic record

VenueArbitration International · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsMcGill University
Fundersnot available
KeywordsTreatyArbitrationJurisdictionLawInvestment (military)Political scienceBilateral investment treatyCompulsory arbitrationPosition (finance)Arbitration clauseLaw and economicsBusinessEconomicsInternational investmentForeign direct investment

Abstract

fetched live from OpenAlex

Abstract Since investors can commonly bring claims under both an international investment treaty and contracts, domestic courts and investment treaty tribunals may compete for jurisdiction over what is—in essence—the same dispute. While much has been written about the distinction between treaty and contract as well as its application in practice, relatively little attention has been paid to the extent of judicial dialogue between domestic courts and investment arbitration regarding this jurisdictional overlap. Investment treaty tribunals have arguably circumvented the issue altogether and show remarkably little restraint when faced with a conflicting contractual forum-selection clause. This current conceptual position presents several issues, however, which domestic courts may encourage arbitral tribunals to overcome. Finding an occasion for more judicial dialogue should therefore not be perceived as an undue encroachment of domestic courts on the autonomous nature of arbitration, but rather as an incentive for investment treaty tribunals to scrutinize the limits of their own jurisdiction more carefully and to start regulating the issue of jurisdictional overlap differently.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.286
Teacher spread0.253 · 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; a candidate call from one teacher head, not a consensus.

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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