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Rural water use and conservation in southwestern Ontario

2000· article· en· W1806134151 on OpenAlexaboutno aff
A. H. Dolan, Reid Kreutzwiser, Rob de Loë

Bibliographic record

VenueJournal of Soil and Water Conservation · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsWater conservationAgricultureLivestockIncentiveBusinessConservation agricultureFarm waterWater useWater scarcityWater savingAgricultural economicsIrrigationNatural resource economicsEnvironmental scienceWater resource managementGeographyEconomicsEcology

Abstract

fetched live from OpenAlex

While Ontario appears to have an abundance of freshwater, shortages occur frequently. Little is known about the nature and extent of use of various water conservation practices in rural areas. Mail-back questionnaire responses from 291 agricultural and rural non farm property owners revealed that most practice some form of water conservation. Analysis indicated that household water saving was more commonly practiced indoors than outdoors. Non farm respondents were more likely to reduce water use through daily behavioral modifications such as shortening shower times, than to install water saving devices in the home. Agricultural respondents were more likely to reduce water waste in the home, primarily by keeping household appliances, pipes, and taps working efficiently. Livestock operators favored water equipment maintenance over all other livestock water saving measures. Irrigators were more likely to adopt a series of conservation measures, most commonly scheduling irrigation and reducing water need of agricultural crops. Statistical analysis revealed that adoption of water conservation measures in the home was best explained by program awareness and participation, level of formal education, and anticipation of future water shortages. Higher levels of livestock water conservation were associated with several factors, including greater farm gross sales and agriculture as the primary income source. Awareness programs aimed at household water conservation may prove effective in rural households, although somewhat less effective in agriculture. Financial incentives to aid in the installation of water saving equipment, along with awareness programs, may be necessary to improve water conservation within the agricultural sector.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.062
GPT teacher head0.184
Teacher spread0.122 · 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.

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

Citations27
Published2000
Admission routes1
Has abstractyes

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