THE DUTY TO COOPERATE IN THE CUSTOMARY LAW OF ENVIRONMENTAL IMPACT ASSESSMENT
Bibliographic record
Abstract
Abstract This article argues that the International Court of Justice's (ICJ) account of the customary law of environmental impact assessment (EIA) is incomplete. While acknowledging the role of the harm prevention principle in formulating the customary obligation to conduct EIAs, the ICJ has ignored the duty to cooperate, notwithstanding the latter duty's equally strong standing in international environmental law. Ignoring the duty to cooperate pushes the court towards a formal and sequential understanding of EIA, which undervalues the centrality of notice and consultation in EIA. In effect, viewed through the harm prevention lens alone, EIA is largely understood in instrumental and technical terms; whereas, if the duty to cooperate is brought back in, EIA's deliberative and ‘other-regarding’ nature is more clearly seen. This, in turn, recognises the normative and political role of EIA in structuring State interactions respecting environmental disputes.
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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 | 0.056 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.057 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.024 | 0.029 |
| Insufficient payload (model declined to judge) | 0.005 | 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".