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Record W4285215142 · doi:10.1017/aju.2022.26

Between Consent and Coherence: Incidental Questions in an Imperfect World

2022· article· en· W4285215142 on OpenAlexaff
Payam Akhavan, Eirik Bjørge

Bibliographic record

VenueAJIL Unbound · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDenialJurisdictionCoherence (philosophical gambling strategy)LawImperfectPolitical scienceSettlement (finance)Law and economicsBalance (ability)PsychologySociologyEconomicsMathematicsPhilosophy

Abstract

fetched live from OpenAlex

International courts and tribunals must maintain a delicate balance between consent and coherence when they consider incidental questions as part of their dispute settlement function. There are compelling reasons, in the contemporary world of unprecedented complexity and interdependence, to instill coherence into dispute settlement procedures, so as to avoid the denial of justice. The exercise of jurisdiction over an “incidental question,” however, must not be forced to the point that it undermines the willingness of states to give their consent to such procedures.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.067
metaresearch head score (Gemma)0.134
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.067
Threshold uncertainty score0.354

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.134
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.086
Scholarly communication0.0160.041
Open science0.0020.014
Research integrity0.0100.014
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.033
GPT teacher head0.277
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2022
Admission routes1
Has abstractyes

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