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Record W4415724032 · doi:10.1111/cag.70030

Prospects for public participation in energy transitions in Canada: Householders' interests in hosting, coordinating, and trading electricity at the local level

2025· article· en· W4415724032 on OpenAlexafffundvenueabout
Ian Rowlands, Chad Walker, Patrick Devine‐Wright, Charlie Wilson, Joseph Fiander, Iain Soutar, Rajat Gupta

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsDalhousie UniversityUniversity of Waterloo
FundersNatural Resources CanadaUK Research and Innovation
KeywordsEnergy transitionPoliticsElectricityEnergy (signal processing)Renewable energyPublic participationControl (management)Public supportSurvey data collection

Abstract

fetched live from OpenAlex

Abstract In Canada, climate change and the rising cost of fossil fuel‐based energy are driving a transition to cleaner local energy systems—combining renewable energy, storage, and smart devices. While these technologies are important, without public support and participation, they will not ensure a just and sustainable transition. In this context, we analyze data from a nationally representative survey (n = 941) of Canadians’ views towards local energy system change, with a focus on three actions (hosting generation, agreeing to external control, and trading electricity) that will be vital. We are interested in overall trends across Canada, though given regional differences and the need to understand the people likely to support these actions, we utilize geographic, socio‐demographic, and political variables to explore variations. In this, four key distinctions were found: females were more likely to support local generation; Quebec residents were more likely to consider coordination by letting an authority take control of their household's appliances; younger Canadians were more interested in all actions; and there was a left‐right divide along political lines, with those supporting left‐leaning parties being more interested in energy management. We locate these findings within broader discussions and close our article with recommendations for further research and policy.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.003
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.018
GPT teacher head0.211
Teacher spread0.192 · 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
Published2025
Admission routes4
Has abstractyes

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