The legacy of the cod fishery collapse: Understanding wind energy acceptance in Newfoundland through energy justice and place
Bibliographic record
Abstract
As renewable energy grows globally, understanding community acceptance of wind energy projects is crucial for ensuring a fair and equitable energy future. Procedural and distributional justice have been widely identified as central to shaping community acceptance. However, there are increasing calls to examine how local historical context plays a role not only in influencing acceptance but also in how residents rationalise their justice considerations. Drawing on energy justice and place attachment/disruption theory, this study investigates how historical experiences with resource development influence perceptions of fairness and acceptance of onshore wind energy in Newfoundland, Canada. Based on semi-structured interviews ( n = 22) and surveys ( n = 146) with residents living near existing wind projects, this study finds high acceptance of current projects (76–100 %), but a distinct pattern of ‘sceptical optimism’ toward future developments. On one hand, residents' attachment to their once-thriving communities and positive experiences with current wind projects contribute to support for future development. On the other, residents' optimism is tempered by hard-learned lessons from the previous resource developments. The findings underscore the need to integrate recognition justice and local historical context more fully into energy justice and acceptance frameworks, highlighting how past (in)justices inform both community support and the evolving understanding of fairness of energy transitions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".