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Record W4402441289 · doi:10.1016/j.erss.2024.103722

Pride of ownership: Local views on community-owned wind energy development in M'Chigeeng First Nation, Canada

2024· article· en· W4402441289 on OpenAlexafffundabout
Carelle Mang‐Benza, Jamie Baxter, Jeff Corbiere

Bibliographic record

VenueEnergy Research & Social Science · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsWestern University
FundersSocial Sciences and Humanities Research Council of CanadaWestern University
KeywordsPrideWind powerBusinessGeographyPolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

This paper draws attention to Indigenous communities who have been understudied in the social acceptance and renewable energy transition literatures. As Canada's federal government endeavors to act towards reconciliation between Indigenous and non-Indigenous citizens, Indigenous communities are taking pioneering roles as owners in the renewable energy sector. In the province of Ontario, M'Chigeeng First Nation is one such pioneer in Ontario's wind energy space, operating as sole owner of two wind turbines since 2012. Our survey of 161 M'Chigeeng members, requested by the community, tests a range of hypotheses that emerged from earlier face-to-face interviews and dovetail with the social acceptance literature. A majority (60 %) of respondents have a positive attitude towards their turbines and while positivity is significantly correlated with most of the hypothesized predictors (e.g., community affinity, fair process, fair benefits, information sharing, pride, relationships (conflict), and reconciliation), the regressions show that positivity towards the turbines is most consistently predicted by positive emotions, pride, and the project representing a form of Indigenous-Settler reconciliation. That said, only 37 % of the sample agree that the project represents reconciliation. The implications of this exploratory case study are discussed in relation to community goals and the wider renewable energy transition.

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)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.007
Science and technology studies0.0050.004
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.120
GPT teacher head0.377
Teacher spread0.257 · 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 designNot applicable
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

Citations2
Published2024
Admission routes3
Has abstractyes

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