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Record W2021474907 · doi:10.4296/cwrj300155

Markets, Policy and the Allocation of Water Resources Among Sectors: Constraints and Opportunities

2005· article· en· W2021474907 on OpenAlexvenueaboutno aff
Theodore M. Horbulyk

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2005
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsnot available
Fundersnot available
KeywordsJurisdictionEnforcementRevenueBusinessSoftware deploymentGovernment (linguistics)Public economicsResource allocationProperty rightsPublic policyEconomicsEnvironmental economicsIndustrial organizationFinanceMicroeconomicsEconomic growthMarket economyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

The paper examines the potential for economic instruments to improve the allocation of water resources across sectors in the economy and identifies the policy issues and policy research that will be prerequisites to achieving this potential. The topic is defined broadly enough to consider current practices and innovative proposals for definition of property rights — that is, for the types of entitlements and activities to which these economic instruments may relate. Consideration is given to issues of jurisdiction within and across levels of government, especially where effective deployment of specific economic instruments might introduce new elements of public revenue and expenditure along with new requirements to exercise regulatory authority and enforcement efforts.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.862
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.003
Scholarly communication0.0060.007
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.011
GPT teacher head0.174
Teacher spread0.163 · 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 designNot applicable
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

Citations17
Published2005
Admission routes2
Has abstractyes

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