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Record W2038406992 · doi:10.4296/cwrj3003197

Measuring Financial Capacity and the Effects of Regulatory Changes on Small Water Systems in Nova Scotia

2005· article· en· W2038406992 on OpenAlexfundvenueaboutno aff
Bettina Lankard Brown, Alfons Weersink, Rob C. de Loë

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2005
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsnot available
FundersCanadian Water NetworkAcadia University
KeywordsNova scotiaNova (rocket)Environmental scienceBusinessFinanceOceanographyGeologyEngineeringAeronautics

Abstract

fetched live from OpenAlex

Municipal water systems are dealing with increasing regulatory compliance costs, aging infrastructure and declining government support. The hypothesized negative effect on financial capacity is assumed to be greatest for rural water systems that have to meet the same quality standards, but with higher marginal service costs and a lower revenue base. This paper examines whether regulatory changes that occurred in the drinking water industry in Nova Scotia in 1995 had negative repercussions on the financial capacity of four rural water suppliers in the Annapolis Valley. The extent of the impacts varies across the four water systems.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.235
Teacher spread0.186 · 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 designObservational
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

Citations12
Published2005
Admission routes3
Has abstractyes

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