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Record W4411806822 · doi:10.1163/18757413_02601014

Counter-Claims before the International Court of Justice: Incidental yet Independent

2023· article· en· W4411806822 on OpenAlexaff
Vladyslav Lanovoy

Bibliographic record

VenueMax Planck Yearbook of United Nations Law · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPublic international lawInternational courtInternational lawLawPolitical scienceEconomic Justice

Abstract

fetched live from OpenAlex

Abstract This article examines the role and practice of counter-claims at the International Court of Justice. Through its procedural rules (Rules of Court) and case law, the Court has clarified the material requirements that govern the admissibility of counter-claims. Nonetheless, several issues concerning their admissibility remain unsettled, namely: (a) the relationship between the Court’s material requirements for the admissibility of counter-claims; (b) the temporal dimension of the first of those requirements, which concerns the Court’s jurisdiction over the counter-claims in question; and (c) the content of the requirement that there be a direct connection between the counter-claims and the subject-matter of the claims in the principal proceedings. These issues bear upon fundamental tenets of the consensual nature of the Court’s jurisdiction and the need to ensure good administration of justice, which calls inter alia for the respect of the procedural equality of the parties and judicial economy. This article offers critical reflections on the Court’s recent case law in which these issues have been raised. It is argued that the key obstacle to the settlement of these issues lies in the hybrid character of counter-claims, which are neither fully independent (autonomous) nor purely incidental in respect of the claims advanced by the applicant in a case.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.248
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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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