Energy democracy, public participation, and support for local energy system change in Canada
Bibliographic record
Abstract
In the face of climate change and associated energy system change, there is a growing literature and more general recognition of the ‘four Ds’ (decarbonization, decentralization, digitalization, and democratization). Yet there has been very little quantitative work that analyzes public perceptions of these changes. Utilizing data from a Canada-wide, nationally representative survey (n = 941), this study conducted provincial and regional assessments to spatially explore the public's views of moves toward innovative local energy system change through the development of what we call Local Smart Grids (LSGs). Through descriptive statistics and t-tests, we sought to answer three main questions: i) To what extent does the public support energy democracy via new local energy systems? ii) What does the public desire in terms of participation? and iii) What motivates the public to participate? We find overall support for energy democracy across Canada, yet varied support among provinces and regions. Canadians seem to want to participate in moves toward energy democracy, although we found a strong preference for more passive participatory actions. Additionally, support and a desire to participate is predominantly motivated by environmental factors, including combating climate change, with community and social motivations playing a secondary role, followed by financial motivations. These findings, some of the first of their kind in the realm of energy democracy in Canada, provide useful insights relevant to scholars, policymakers, and practitioners working on LSG implementation as well as others with an interest in socio-technical innovation and energy system change.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".