Sun, wind or water? Public support for large-scale renewable energy development in Canada
Bibliographic record
Abstract
Public acceptance is one important aspect of broader social acceptability of renewable energy. Using a national, representative survey dataset of Canadian citizens (n = 1407), we examine public support for three infrastructure-scale renewables: large hydropower, wind farms, and solar farms. Few studies compare acceptance of multiple technologies or acceptance across sub-national regions. Due to differing levels of historical and current development of energy technologies, the Canadian provinces of Alberta, British Columbia, Ontario and Quebec provide a unique case for comparison. At the national level, results demonstrate strong support and high levels of familiarity for these renewable technologies, but limited belief they will lower greenhouse gas emissions. Lower levels of support for wind and hydro technologies were seen in provinces that recently experienced development. Using regression analysis, we found support for each of the technologies was influenced by a different set of factors. Important influencing factors included environmental and climate concern, familiarity with the technology, personal values, political affiliation, gender, age and education.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".