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Record W4377102825 · doi:10.1016/j.egyr.2023.05.027

Assessing motivations and barriers to renewable energy development: Insights from a survey of municipal decision-makers in Alberta, Canada

2023· article· en· W4377102825 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnergy Reports · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsUniversity of Alberta
FundersCanada First Research Excellence FundUniversity of Alberta
KeywordsRenewable energyContext (archaeology)Energy transitionEnvironmental economicsBusinessGovernment (linguistics)Environmental planningEnvironmental resource managementEconomicsEngineeringGeography

Abstract

fetched live from OpenAlex

Municipal renewable energy development is a component of community energy that remains under-examined. Particularly, within jurisdictions like Alberta, Canada, where fossil fuels remain dominant, transition to decentralized and renewable energy systems can be challenging. To gain a deeper understanding of the motivations and the barriers to building renewable energy projects within municipalities, we utilize a province-wide survey of municipal decision-makers (n = 101). Results are examined through a framework that combines the theory of planned behaviour with transition theory to identify specific motivations and challenges associated with renewable energy development in this jurisdiction. Consistent with other research, results highlight the perception of economic value that encourages municipal renewable development. Key constraints on the development of renewable projects are associated with difficulties in accessing grants, limited support from the provincial government, and a concern about aesthetics and negative impacts on natural landscapes. Results are discussed in the context of published literature on this topic, with insights on the value of this blended theoretical framework for unpacking and understanding constraints and opportunities for renewable energy development at the municipal level.

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)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.255
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
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 head0.020
GPT teacher head0.281
Teacher spread0.260 · 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