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Record W1580764330

Once Around the Hemispheric Waterfront: Five Issues and Five Themes

2006· article· en· W1580764330 on OpenAlexaff
Jamie Benidickson

Bibliographic record

VenueSSRN Electronic Journal · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSanitationWater securityCorporate governanceEnvironmental planningIntegrated water resources managementBusinessWater supplyIndigenousWater qualityWater tradingAquiferWater resourcesWater industryGroundwaterWater resource managementNatural resource economicsGeographyWater conservationEnvironmental scienceEngineeringEconomicsEnvironmental engineeringFinanceEcology
DOInot available

Abstract

fetched live from OpenAlex

This paper surveys five basic issues in water governance that arise in legal regimes throughout the western hemisphere: 1) dam construction; 2) diversion, inter-basin transfer and exporting water; 3) ground water management and sustainable exploitation of aquifers; 4) maintaining security of municipal drinking water supplies; 5) universal access to improved sanitation and wastewater management. The author illustrates these issues and themes with examples of water management in the Americas. Four general themes emerge from surveying water governance in the Americas. Regimes are facing tensions between individual water rights and pressure to privatize water, and the public interest in maintaining a sustainable water supply. Inter-jurisdictional co-operation and an institution for jointly managing cross-border water basins are becoming increasingly important, given the number of basins that cross national borders in the Americas. Climate change is beginning to add stresses on the quality and availability of water. Assuming that access to water is a human right, governments need to respond to disparities in access to safe water in indigenous communities. Finally, privatizing water could enable national water resources to be internationally traded on private markets.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.243
Teacher spread0.238 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2006
Admission routes1
Has abstractyes

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