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Record W4289832146 · doi:10.1163/18760759-43010002

International Environmental Law: of Sovereignty, Complexity, and Grotian Moments

2022· article· en· W4289832146 on OpenAlexaff
Jutta Brunnée

Bibliographic record

VenueGrotiana · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInternational lawSovereigntyLawPublic international lawEnvironmental lawPolitical scienceTreatyState (computer science)Municipal lawLaw and economicsSociologyComputer science

Abstract

fetched live from OpenAlex

Abstract The Grotian Moment concept provides a lens through which to reflect on the enduring hold of state sovereignty on international environmental law. The article traces the development of the field’s customary rule framework and canvasses efforts to push its conceptual boundaries beyond the inter-state paradigm. Given their dominant role in the field, the article then provides a brief overview of treaty-based approaches to the development of international environmental law. It focuses on the global response to the climate emergency, as illustrative of how international environmental law has evolved in response to the challenges posed by complex crises. The article concludes by suggesting that international environmental law is unlikely to see a Grotian Moment at the level of customary international law, but that it does hold potential for the new thinking and new approaches that could produce a ‘quasi’ Grotian Moment.

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)0.007
metaresearch head score (Gemma)0.010
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: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.068
Scholarly communication0.0140.016
Open science0.0010.007
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.275
Teacher spread0.249 · 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
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

Citations1
Published2022
Admission routes1
Has abstractyes

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