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Record W2274118816 · doi:10.1017/s0069005800010109

Les piliers économique et environnemental du développement durable: conciliation ou soutien mutuel? L’éclairage apporté par la Cour internationale de Justice dans l’Affaire des Usines de pâte à papier sur le fleuve Uruguay (Argentine c Uruguay)

2011· article· fr· W2274118816 on OpenAlexvenueno aff
Géraud de Lassus Saint-Geniès

Bibliographic record

VenueCanadian Yearbook of international Law/Annuaire canadien de droit international · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesConciliationPhilosophyLawArbitration

Abstract

fetched live from OpenAlex

Sommaire La façon dont les divers acteurs de l’ordre juridique international ont appréhendé la relation entre les piliers économique et environnemental du développement durable témoigne d’une évolution: alors qu’une première interprétation estimait que cette relation se fondait sur la recherche d’une conciliation, une seconde interprétation a par la suite considéré qu’elle était au contraire caractérisée par l’existence d’un soutien mutuel. Si cette seconde conception, qui conduit à extraire du développement durable toute idée de tension entre l’environnement et l’économie, a connu une influence grandissante au cours des dernières années, la Cour internationale de Justice a réaffirmé dans l’ Affaire des Usines de pâte à papier sur le fleuve Uruguay son attachement à la première interprétation de la relation entre les piliers économique et environnemental. Il semble donc actuellement coexister en droit international deux lectures opposées du développement durable, l’une se fondant sur le paradigme de la conciliation, l’autre sur le paradigme du soutien mutuel.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.032
GPT teacher head0.242
Teacher spread0.209 · 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
Published2011
Admission routes1
Has abstractyes

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