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Record W2595339070 · doi:10.1163/22119000-12340034

Sustainability Impact Assessments as Inputs and as Interpretative Aids in International Investment Law

2017· article· en· W2595339070 on OpenAlexaff
Markus W. Gehring, Sean Stephenson, Marie‐Claire Cordonier Segger

Bibliographic record

VenueThe Journal of World Investment & Trade · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Arbitration and Investment Law
Canadian institutionsCentre for International Governance InnovationUniversity of Waterloo
Fundersnot available
KeywordsTreatyNegotiationInvestment (military)SustainabilityArbitrationSustainable developmentInternational tradeBusinessEconomicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Sustainability impact assessments (SIAs) act as bridges between trade and investment agreements and social, environmental and human considerations. They are relevant as inputs into the treaty negotiation process and as interpretive aids in investment treaty arbitration. As inputs, SIAs attempt to measure the impact of environmental, social, economic and human rights aspects of trade and investment agreements prior to and during a treaty’s negotiation. SIAs have been performed on all major negotiations in the EU since 1999, and will continue to be performed under its investment competence. Case studies in this article demonstrate how SIAs may include climate change. Additionally, legal recommendations are offered which, if adopted by the Directorate General for Trade, should increase the effectiveness of SIAs. As interpretive aids, SIAs may be key references in treaty interpretation arguments in light of increased environment and development related investment disputes and focus on sustainable development policy space.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.326
Teacher spread0.307 · 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 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

Citations7
Published2017
Admission routes1
Has abstractyes

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