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Record W4307631116 · doi:10.5539/ilr.v11n1p351

Ascertaining the Juridical Basis of International Law by Analyzing the Move-structures of Treaties: A Possible Linguistics-oriented Exploration?

2022· article· en· W4307631116 on OpenAlexvenueno aff
Hongwu Yin, Hao Sheng

Bibliographic record

VenueInternational Law Research · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsnot available
FundersHunan Normal University
KeywordsInternational lawLawPolitical scienceTreatyApplied linguisticsLinguisticsComparative lawSociologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Treaties (conventions), international custom and the general principles of law generally constitute the formal sources of international law. The present linguistics-oriented study of exploring the juridical basis of international law specifically focuses on analyzing that of treaties. An empirical study of the linguistic expressions and forms of the treaties is supposed to probe into what the contracting parties really think when adopting the treaty texts. It applies the move structure approach of English linguistics for the purpose of ascertaining the juridical basis of treaties. After the generalization of a prototypical six-move-structure existing in treaties, this article specially makes a focal study on the second and third moves of the treaties, managing to find out the linguistic evidence of ascertaining the juridical basis of the treaties. “The Contracting Parties’ Shared Conviction in Common Good as opinio juris” in Step 1 of “Move 2 Establishing Contextual Foundations for the Present Legislation” is ascertained as the juridical basis of international law from the linguistics-oriented perspective.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.957
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.334
Teacher spread0.287 · 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
Published2022
Admission routes1
Has abstractyes

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