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Record W3174979888

Beyond Equity: Shared Natural Resources and Human Rights, Criminal Law, and the Use of Force

2021· article· en· W3174979888 on OpenAlexaff
Eian Katz

Bibliographic record

VenueeYLS (Yale Law School) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsCanmore Museum and Geoscience Centre
Fundersnot available
KeywordsHarmLawEquity (law)Political scienceJurisdictionHuman rightsNatural resourceLaw and economicsSubstantive lawInternational lawCriminal lawSociology
DOInot available

Abstract

fetched live from OpenAlex

Transboundary resource disputes are often analyzed by reference to two nebulous and conflicting principles that have emerged in international environmental law: “equitable and reasonable utilization” and “no significant harm.” Frequently overlooked in this context is the potential value of other canons of international law—especially human rights law, criminal law, and the rules governing the use of force—in adding definition to the muddled contours of these foundational precepts. This Article therefore undertakes an assessment of sovereign rights and obligations regarding shared natural resources which arise from these other bodies of law. In doing so, it offers new lenses through which to evaluate competing state resource claims. It also provides fresh perspective on longstanding controversies in international law relating to extraterritorial jurisdiction, conflict of rights, and non-military attacks or uses of force.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.058
Scholarly communication0.0100.015
Open science0.0010.008
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.034
GPT teacher head0.301
Teacher spread0.267 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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