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Record W43856880

Impact of energy conservation on electricity sales

2006· article· en· W43856880 on OpenAlexaff
K.H. Tiedemann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicEnergy, Environment, and Transportation Policies
Canadian institutionsBC Hydro (Canada)
Fundersnot available
KeywordsElectricityEnergy conservationEconometric modelEnvironmental economicsElectricity generationEconometricsEconomicsPower (physics)BusinessEngineering
DOInot available

Abstract

fetched live from OpenAlex

This paper has two main purposes. The first purpose is to develop a simple model of an economy without external effects, extend this model to include pollution as an external effect or distortion, and further extend this model to include energy conservation as an instrument to reduce pollution. The second purpose of this paper is to estimate the impact of BC Hydro's Power Smart energy conservation program on electricity sales using econometric methods. There are three main empirical results. First, the relationship between electricity sales and key drivers can be successfully modelled using a relatively simple framework estimated using maximum likelihood methods. Power Smart reduced electricity sales by about 2,320 GWh per year by 2000, or about 93% of program estimates of Power Smart's impact. Third, the large estimated program impacts generated by alternative models suggest the importance of careful model specification in attempting to estimate energy conservation program impacts.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.010
GPT teacher head0.233
Teacher spread0.224 · 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
Published2006
Admission routes1
Has abstractyes

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