Bio-Piracy on the High Seas? Benefit Sharing from Marine Genetic Resource Exploitation in Areas beyond National Jurisdiction
Bibliographic record
Abstract
Transnational benefit sharing from the exploitation of Marine Genetic Resources’ (MGR’s) in Areas Beyond National Jurisdiction (ABNJ) presents a unique problem in international law. Proposals to govern MGR’s in ABNJ include leaving them unregulated, governance under the International Seabed Authority (ISA) or the Convention on Biological Diversity (CBD) or implementing a new international regime. This paper demonstrates that a hybrid solution for MGR governance under the ISA which is modeled on the CBD and The Nagoya Protocol (Nagoya), provides the most adroit solution to the problem of equal benefit and access to MGR’s for all States. This solution ensures adequate conservation of MGR’s, meanwhile fostering sustainable exploitation and maintaining equality in access, biodiversity and the sharing of financial and technological benefits amongst the internationalcommunity. Further, examining benefit sharing from bioprospecting under the CBD and Nagoya provides a foundation for a benefit-sharing regime in ABNJ under The United Nations Convention on the Law of the Sea (UNCLOS). Examining the CBD, Nagoya and UNCLOS demonstrates how benefits arising from exploitation of MGR’s in the high seas and deep bed should be included as a mandate of the ISA. This methodology is accomplished by focusing on bioprospecting for MGR’s and how the CBD and Nagoya facilitate access to the resource while ensuring that the host State or community benefits from granting access. As the CBD and Nagoya focus on benefit sharing in light of national sovereignty, and UNCLOS regulates in areas beyond national jurisdiction, the ISA is perfectly placed to adopt the principles of the CBD and Nagoya and provide a mechanism to ensure that MGR’s in ABNJ are adequately conserved and the benefits arising from their exploitation equitably shared.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".