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Record W4413841237 · doi:10.1016/j.erss.2025.104274

The legacy of the cod fishery collapse: Understanding wind energy acceptance in Newfoundland through energy justice and place

2025· article· en· W4413841237 on OpenAlexfundaboutno aff
Jessica Hogan

Bibliographic record

VenueEnergy Research & Social Science · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsnot available
FundersUniversity of St AndrewsBanco SantanderSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of CanadaFundación Banco Santander
KeywordsFisheryEnergy (signal processing)Economic JusticeWind powerOceanographyEnvironmental scienceEngineeringPolitical scienceGeologyLawPhysicsBiology

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.009
Science and technology studies0.0100.012
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.067
GPT teacher head0.387
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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