Integrating Environmental Impact Assessments into International Investment Agreements: Global Administrative Law and Transnational Cooperation
Bibliographic record
Abstract
Environmental Impact Assessment (EIA) is a legal device used by many States to protect the environment. Such assessments can bring foreign investors into conflict with host State regulators and civil society. When this occurs, an investor may seek to protect its investment against the consequences of EIA by pursuing remedies under an international investment agreement (IIA). The purpose of this article is to examine the role of IIAs in maintaining and supporting the integrity of the EIA process of the host State. It focuses on ways to integrate EIA into IIAs in order to strengthen the State’s ability to protect the environment. The article examines recent case law to identify ways in which EIA can give rise to investor-State claims under IIAs. It also discusses two theoretical models that are useful for designing reforms: the global administrative law paradigm and the cooperative transnational approach.
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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 | 0.026 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.016 | 0.021 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".