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Record W4401177936 · doi:10.1163/22119000-12340328

Sustainable Development as a Wicked Problem in Investment Arbitration

2024· article· en· W4401177936 on OpenAlexaff
Ksenia Polonskaya, Jean‐Michel Marcoux

Bibliographic record

VenueThe Journal of World Investment & Trade · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsCarleton University
Fundersnot available
KeywordsArbitrationAdjudicationSustainable developmentSustainabilityDispute resolutionRespondentLaw and economicsInvestment arbitrationInvestment (military)Relevance (law)PoliticsPolitical scienceGeneral assemblyCommissionInvestor-state dispute settlementBusinessLawInternational investmentEconomicsForeign direct investment

Abstract

fetched live from OpenAlex

Abstract References to ‘sustainable development’ and ‘sustainability’ can be found in decisions of investment arbitration tribunals and submissions from disputing parties. By relying on the concept of ‘wicked problem’, this article highlights the failure to articulate any clear relevance of sustainable development in the adjudication of investment disputes and structural limitations imposed by investor-State dispute settlement (ISDS). It proceeds in four steps. First, the article defines wicked problems and their distinguishing properties. Second, it shows how tribunals have used sustainable development in a way that evidences these distinguishing properties. Third, in light of submissions from respondent States and claimants, the article shows that ISDS imposes structural limitations on narratives that relate to sustainability and sustainable development. Finally, it examines the discussions on sustainability under the umbrella of the United Nations Commission on International Trade Law Working Group III and stresses the need for a political resolution outside ISDS proceedings.

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)0.058
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.081
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0100.065
Scholarly communication0.0240.021
Open science0.0030.017
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.234
Teacher spread0.218 · 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 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
Published2024
Admission routes1
Has abstractyes

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