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Record W4385875551 · doi:10.24908/ijesjp.v10i1.16050

Energy Justice and Territory: Present and Futures of Wind Energy in Brazil

2023· article· en· W4385875551 on OpenAlexvenueno aff
Veronica Olofsson

Bibliographic record

VenueInternational Journal of Engineering Social Justice and Peace · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsnot available
FundersInstitut écologie et environnementStockholms Universitet
KeywordsFraming (construction)Wind powerRenewable energyClimate change mitigationFutures contractPolitical scienceGreenhouse gasEnvironmental resource managementGeographyEnvironmental scienceBusinessCivil engineeringEngineering

Abstract

fetched live from OpenAlex

Transitioning towards renewable energy sources is crucial in mitigating climate change and reducing greenhouse gas emissions. Global energy consumption is expected to increase 50 % by 2050, meaning one of today’s main challenges is complying with those demands without tampering with the uncertainties of global climate change. To address climate change renewable energy sources are essential and wind power plays a great role in the energy matrix. Brazil is one of the front runners in the energy transition, where wind power has expanded since the early 2000’s. The state of Bahia, in Northeastern Brazil, is currently the region where wind energy is expanding the most. However, conflicts related to territoriality and justice aspects are increasing in the state due to the fast-expanding wind energy sector. This study applies document and content analysis to explore the multiple narratives regarding the wind energy expansion in the state of Bahia, Brazil. Framing theory and theories addressing power struggles and conflicts in relation to the energy transition will guide the analysis of the documents included in the material. Based on the analysis of the Bahian case, this study shows that different actors frame the matter of wind energy expansion differently depending on their positionings. Civil society and local perspectives are not present in policies and decision-making processes, including the planning and installation of wind energy parks in the studied case. The results suggest that inclusion and participation of local actors, stakeholders and the civil society is essential to ensure a just and sustainable transition to clean energy sources.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.294
Teacher spread0.283 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2023
Admission routes1
Has abstractyes

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