Strategic Environmental Assessment in Marine Areas beyond National Jurisdiction: Implementing Integration
Bibliographic record
Abstract
Abstract Whereas environmental impact assessment (EIA) is broadly accepted as a legal requirement for managing the marine environment in areas beyond national jurisdiction (ABNJ), there has been a greater reluctance by States to adopt strategic environmental assessment (SEA) requirements. This suggests the legal basis for SEA is different and less firmly established in international law than EIA. This article examines the distinct legal and policy roles of SEA in managing ABNJ, which then informs our understanding of its legal basis. We argue, unlike EIA’s close association with due diligence obligations to prevent harm, SEA is better understood as a legal mechanism for the implementation of the principle of integration. Recognised as central to marine governance, integration has normative dimensions that must be addressed by States. SEA, we argue, is well-suited to this task. This article addresses SEA for ABNJ generally, but attention is paid to negotiations regarding marine biodiversity of ABNJ.
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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 | 0.021 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".