Equitable sharing of deep-sea mining benefits: More questions than answers
Bibliographic record
Abstract
The International Seabed Authority is tasked to develop rules for “equitable sharing of financial and other economic benefits” from deep-sea mining activities in the seabed area beyond national jurisdiction. Without this element of the legal regime, the ISA cannot meet its stated aim of ensuring deep-sea mining activities are undertaken for the ‘benefit of [hu]mankind as a whole’, with particular consideration to the interests and needs of developing States. This paper examines proposals made at the ISA to date. It demonstrates, using modelled revenue estimates, that the direct distribution of funds would lead to States receiving economically insignificant benefits. It also examines formulae for dividing benefits between member States, noting a degree of arbitrariness in current proposals. The authors note the merit of an alternative proposal for pooling mining revenue into a ‘Seabed Sustainability Fund’, but question whether, as is currently proposed, the fund should be narrowly focused on deep-sea mining related activities, including activities that should be funded by miners, and/or before mining commences. In addition, aspects of the fund’s proposed governance are examined critically against international best practice. The paper finally raises the importance of the decision-making process for equitable benefit-sharing arrangements meeting the highest standards of process legitimacy, including transparency and consultation. The paper notes that these are decisions about the common heritage of [hu]mankind, which include value questions on which there may be diverse positions, and that set a precedent for other global common resources in the future.
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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 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.013 | 0.046 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 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".