Operationalizing strategic environmental assessment under the BBNJ Agreement: legal frameworks, national practices, and implementation pathways
Bibliographic record
Abstract
The conclusion of the BBNJ Agreement marks a pivotal advancement in the development of the international law of the sea, particularly through the integration of Strategic Environmental Assessment (SEA) into the governance of areas beyond national jurisdiction. This article analyzes the requirements of SEA under the BBNJ Agreement and explores the potential challenges for states to meet its requirements by critically examining the legal frameworks and national practices on SEA in the European Union, the United States and Canada, and Pacific Small Island Developing States. It identifies persistent challenges such as legal fragmentation, disparities in institutional and technical capacity, and the absence of coordinated implementation mechanisms across jurisdictions in current SEA practices. The practice of SEA in ABNJ remains disjointed, hindering the formation of a cohesive international regime. To address these gaps, the article advances three strategic recommendations: (1) the development of non-binding technical guidance by the BBNJ Agreement’s Scientific and Technical Body to promote harmonized SEA practices; (2) the establishment of international coordination mechanisms to resolve conflicts between national and sectoral SEA rules; (3) the embedding of SEA-specific capacity-building and technology transfer support into the Agreement’s implementation architecture to empower developing states; and (4) leveraging Marine Protected Areas under the BBNJ framework as entry points for operationalizing SEA. As of 2024, MPAs cover only about 1.45% of the total ABNJ surface. Incorporating SEA into the planning and management of these MPAs under the BBNJ regime can support more transparent and evidence-based expansion efforts, contributing to the achievement of the global 30×30 target. These approaches aim, as outlined above, to overcome structural and normative barriers while enhancing the role of SEA in protecting marine biodiversity and ensuring sustainability in 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 | 0.064 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".