From Fact to Applicable Law: What Role for the International Climate Change Regime in Investor-State Arbitration?
Bibliographic record
Abstract
Abstract While many investor-state dispute settlement (ISDS) proceedings based on international investment agreements have dealt, directly or incidentally, with environmental issues, state measures relating to the mitigation and adaptation to climate change have been subject to a small number of reported cases. This article demonstrates that there is a significant gap between the number of investor-state disputes having a direct relevance with climate change, on the one hand, and the number of such cases that have actually raised climate change as a material legal or factual issue. In addition, arbitral tribunals faced with disputes related to measures or sectors that are of direct relevance to climate action have, to date, virtually never engaged in any sort of substantial analysis of international climate change treaties and related instruments, rules, or practices. Against this backdrop, this article will explore ways for arbitrators and parties to ISDS proceedings to better consider the climate regime — in particular, the Paris Agreement and instruments arising therefrom — in ISDS proceedings beyond its current limited role as an element of context. While the literature has mostly focused on integrating climate change concerns in ISDS, this article goes further by exploring how states’ international climate obligations could play a greater role in the adjudication of investor-state disputes, including by providing states with a justification for implementing more ambitious regulations as well as tribunals with guidance for interpreting substantive obligations in investment treaties.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.035 |
| Scholarly communication | 0.029 | 0.021 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".