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Record W4411700980 · doi:10.9790/487x-2706133747

Curtailment, Sustainability, and Governance: The Strategic Role of Renewable Energy Sources within the ESG Framework

2025· article· en· W4411700980 on OpenAlexfundno aff
Sueli Aparecida de Oliveira, Ana Katherine Silveira Pereira Caracas

Bibliographic record

VenueIOSR Journal of Business and Management · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
FundersDirectorate for Biological SciencesFondation Pour La Conservation Du Saumon Atlantique
KeywordsSustainabilityCorporate governanceBusinessRenewable energyEnvironmental economicsIndustrial organizationEconomicsFinanceEngineeringEcology

Abstract

fetched live from OpenAlex

Background: The global expansion of renewable energy sources in the electricity matrix has intensified the challenges related to curtailment, which refers to the restriction of energy production due to technical, regulatory, or economic factors. Although rarely addressed explicitly, this phenomenon has direct consequences for the sustainability and efficiency of power systems, requiring new governance strategies aligned with Environmental, Social, and Governance (ESG) principles. In this context, the study investigates the strategic role of renewable energy in promoting more sustainable and resilient curtailment management, emphasizing its relevance to the energy transition and the development of management models suited to current climate challenges. Materials and Methods: This research employed a qualitative methodology based on epistemological principles that value the analysis of social phenomena within their specific historical and institutional contexts. It is classified as a theoretical-analytical study, grounded in a review of international scientific and technical literature, and focused on the intersection of curtailment, energy sustainability, and governance within the ESG framework. Results: The main objective of the study was to analyze the relationship between renewable energy curtailment and ESG principles, while proposing scientifically grounded and strategic guidelines for sustainable curtailment

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.229
Teacher spread0.206 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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