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Record W4230512288 · doi:10.32920/ryerson.14662113

A multi-country study of household energy saving behaviour

2021· preprint· en· W4230512288 on OpenAlexaffabout
Ela Tabaku

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnergy
TopicEnergy Efficiency and Management
Canadian institutionsToronto Metropolitan UniversityUniversity of Manitoba
Fundersnot available
KeywordsProbit modelElectricityConsumption (sociology)CzechEnergy consumptionMultivariate probit modelEconomicsOrdered probitBusinessProbitEnergy (signal processing)Energy conservationDemographic economicsPublic economicsEconomic growthEconometrics

Abstract

fetched live from OpenAlex

Due to the increased worldwide demand for electricity, governments and policy makers are looking to identify tools to help reduce household energy consumption. This study examines the relationship between the empirical and attitudinal variables and the likelihood of implementation of household energy conservation measures and investments, using a wide data set involving household level characteristic from 10,252 respondents from ten different countries (Australia, Canada, Czech Republic, France, Italy, Korea, Mexico, Netherlands, Norway, and Sweden). Moreover, the effects of time varying electricity pricing on household energy saving measures and investments is evaluated. Using the multivariable probit model, this project makes comparison across the ten countries incorporating socio-demographic characteristics, and allows for the potential correlation between energy saving decisions (measures and investments).

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)0.002
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.035
GPT teacher head0.259
Teacher spread0.225 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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