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Record W4327976859 · doi:10.1016/j.marpol.2023.105572

Equitable sharing of deep-sea mining benefits: More questions than answers

2023· article· en· W4327976859 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMarine Policy · 2023
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of Waterloo
FundersPew Charitable Trusts
KeywordsTransparency (behavior)RevenueJurisdictionBusinessCorporate governanceSustainabilityPolitical scienceEnvironmental resource managementEnvironmental planningEconomicsGeographyLawFinance

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.257
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it