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The Effect of Feedback by Text Message (SMS) and Email on Household Electricity Consumption: Experimental Evidence

2010· article· en· W2131789327 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Energy Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsnot available
Fundersnot available
KeywordsElectricityConsumption (sociology)Quarter (Canadian coin)Control (management)Short Message ServiceBusinessAdvertisingEconomicsComputer scienceEngineeringTelecommunicationsGeography

Abstract

fetched live from OpenAlex

This paper analyzes the effect of supplying feedback by text messages (SMS) and email about electricity consumption on the level of total household electricity consumption. An experiment was conducted in which 1,452 households were randomly allocated to three experimental groups and two control groups. Feedback was supplied throughout 2007 to members of the experiment groups who accepted the invitation, and data on consumption of electricity for 2006 and 2007 collected for all participants and control group members. 30% of the households invited to receive feedback accepted the invitation. Results suggest that email and SMS messaging that communicated timely information about a household’s ‘exceptional’ consumption periods (e.g. highest week of electricity use in past quarter) produced average reductions in total annual electricity use of about 3%. The feedback technology is cheap to implement and therefore likely to be cost-effective.

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.

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 categoriesnone
Consensus categoriesnone
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 score0.221
Threshold uncertainty score0.390

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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