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Record W4229001697 · doi:10.3390/su14031902

Who Makes or Breaks Energy Policymaking in the Caribbean Small Island Jurisdictions? A Study of Stakeholders’ Perceptions

2022· article· en· W4229001697 on OpenAlexaff
Xiaoyu Liu, Jahan Ara Peerally, Claudia De Fuentes, David Ince, Harrie Vredenburg

Bibliographic record

VenueSustainability · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsHEC MontréalUniversity of CalgarySaint Mary's University
Fundersnot available
KeywordsSustainabilityMandateContext (archaeology)ElectricityBusinessPublic economicsEconomicsPolitical scienceGeographyEngineering

Abstract

fetched live from OpenAlex

While most studies view small island economies as a homogenous group with multiple similar vulnerabilities, few studies argue that they are a heterogenous group due to their political jurisdictions (independent versus dependent economies), with mostly environmental vulnerabilities in common. Departing from these two premises, our study is the first empirical attempt at examining inter-small island jurisdiction (SIJ) heterogeneity from the social construct perspective of stakeholders’ perceptions and within the context of environmental sustainability and energy policymaking. We quantitatively explore, across 34 Caribbean SIJs, multiple stakeholders’ perceptions of the influence of the electricity sector as a leader in environmental performance. The results show that when the governments of independent SIJs exclude electricity sector stakeholders and include other primary energy stakeholders in energy policymaking, the electricity sector actors are better perceived as leaders in environmental performance. In a global context where inclusiveness is important for sustainability, this finding suggests that within the systemic contexts of SIJs, stakeholders view the exclusion of powerful incumbent energy actors from policymaking as a viable approach for moving the environmental sustainability mandate forward. Our study has implications for policymakers and scholars on the democratic process of policymaking, and for practitioners in terms of building social trust.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.161
GPT teacher head0.360
Teacher spread0.198 · 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.

Study designQualitative
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
Published2022
Admission routes1
Has abstractyes

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