Those who support wind development in view of their home take responsibility for their energy use and that of others: evidence from a multi-scale analysis
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.
Bibliographic record
Abstract
While shifting electricity production to renewable sources is of critical importance in addressing global climate change, the costs of such development are often felt locally. This study explores what leads to support for wind development when respondents are asked to think about three different geographic scales: general, regional and within view of their home. Research was conducted in the Chignecto area of Atlantic Canada, a semi-rural area in which a prominent 15-turbine wind farm was constructed in 2012. A random population mail-out survey achieved a response rate of 40%. Questions explored exposure to wind turbines; support for wind energy development; place attachment; beliefs concerning the distribution of energy and benefits; and demographics. While most predictors of support are significant in bivariate correlations, many commonly used predictors of wind support, such as place attachment or community benefits, disappear or weaken under controls as predictors of support at smaller scales. Novel predictors of support inspired by climax thinking emerged as stronger at more local scales, including support for energy export beyond local needs and agreement that wind turbines provide a reminder of energy use. These results suggest new pathways for understanding support for wind development within the communities most directly affected.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it