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Record W2062785833 · doi:10.3390/w5041865

Perceptions of Water Ownership, Water Management, and the Responsibility of Providing Clean Water

2013· article· en· W2062785833 on OpenAlexafffund
Jacqueline Noga, Gregor Wolbring

Bibliographic record

VenueWater · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Calgary
FundersGenome AlbertaGenome Canada
KeywordsWater scarcityWater usePerceptionWater conservationQualitative propertyResource (disambiguation)Water resourcesQualitative researchPsychologyBusinessPublic relationsEnvironmental economicsSocial psychologyEnvironmental resource managementMarketingSociologyEconomicsPolitical scienceEcologySocial scienceComputer science

Abstract

fetched live from OpenAlex

Perceptions of water and water related issues still render many under-researched topics. This study aims to further our knowledge regarding people’s perceptions of water and our understanding about the different ways individuals use water. The authors asked the question: Does the way an individual perceives water (i.e., as a commodity, a human right, private resource, public resource and/or natural resource) influence consumption and conservation of water, and sentiments towards control and allocation of water? An exploratory online questionnaire was designed to generate qualitative and quantitative data of survey participants’ perceptions, beliefs and actions towards water issues, such as overconsumption and scarcity. Data analysis included comparison of the quantitative data regarding the non-statistical association between how an individual perceives water and the individual’s beliefs, as well as qualitative analysis of the comments using an iterative pattern coding technique. One hundred and sixty four individuals participated in the survey (75% completion rate) and over 430 comments were made. Themes that emerged from the comments included: responsibility, scarcity, the value of water, knowledge gained and education needed. Comparison of the different perceptions of water revealed that different perceptions of what water is resulted in different beliefs about what the cost of water should be. These findings have implications for future water use, including what needs to change in order to increase appreciation for water issues.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.001

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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations34
Published2013
Admission routes2
Has abstractyes

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