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Record W2061329264 · doi:10.1080/07900620500108494

Water Allocation among Multiple Stakeholders: Conflict Analysis of the Waiahole Water Project, Hawaii

2005· article· en· W2061329264 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

VenueInternational Journal of Water Resources Development · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGame Theory and Voting Systems
Canadian institutionsUniversity of WaterlooUniversity of Windsor
Fundersnot available
KeywordsWater resourcesDitchPopulationWater tradingCompetition (biology)BusinessResource allocationOptimal allocationWater resource managementNatural resource economicsEconomicsWater conservationEnvironmental scienceManagementSociologyEcology

Abstract

fetched live from OpenAlex

Recent years have seen a sharp increase in the demand for water in Hawaii, which has intensified and accelerated the competition for the state's water resources. Specifically, this paper uses the decision support system GMCR II to analyse the strategic aspects of a multi-party water dispute involving the allocation of Waiahole Ditch waters on Oahu, the major economic and population centre of Hawaii. The issue of surplus water allocation is unprecedented in Hawaii and thus there is no explicit water law precedent governing allocation of such water as conceived by the water administrative agencies or the judicial branch.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.065
GPT teacher head0.241
Teacher spread0.176 · 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