Assessing motivations and barriers to renewable energy development: Insights from a survey of municipal decision-makers in Alberta, Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".