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Record W3120428254 · doi:10.5539/jpl.v14n2p84

Addressing Fragmentation and Inconsistency in International Environmental Law Analysis of the Role of Specialised or Treaty Judicial Bodies

2021· article· en· W3120428254 on OpenAlexvenueno aff
Dieudonné Mevono Mvogo

Bibliographic record

VenueJournal of Politics and Law · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicInternational Environmental Law and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsFragmentation (computing)TreatyInternational courtPolitical scienceLaw and economicsLawCentripetal forceState (computer science)International lawSociologyPublic international lawComputer scienceMechanicsPhysicsBiologyEcology

Abstract

fetched live from OpenAlex

This paper analyses the contribution of treaty or specialised judicial bodies to striking problems such as fragmentation and inconsistency within International Environmental Law (IEL) as they fill the gaps in IEL, taking advantage of the absence of an overarching International Environmental Court (IEC) and the indolence of the International Court of Justice (ICJ). It argues that by helping improve the ICJ, they will help resolve IEL's jurisprudential inconsistency and fragmentation. The paper therefore first explains the sense in which jurisprudential fragmentation and inconsistency underline IEL's compliance mechanisms, and shows the limits of the state-centripetal approach of the ICJ as a solution to such a problem. Finally, it proposes a state-centrifugal paradigm that stresses how international specialised judicial bodies may help strengthen the ICJ's fragmentation and inconsistency management functions. To propose this novel approach, this paper employs legal critical methods to expose current gaps in the state-centripetal approach.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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 designObservational
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

Citations2
Published2021
Admission routes1
Has abstractyes

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