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Record W3117316283 · doi:10.1111/apv.12296

Beyond electrification for development: Solar home systems and social reproduction in rural Solomon Islands

2020· article· en· W3117316283 on OpenAlexfundno aff
Stephanie Ketterer Hobbis

Bibliographic record

VenueAsia Pacific Viewpoint · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRural electrificationEconomic growthElectrificationDistrustPolitical scienceSociologyDevelopment economicsGeographyElectricityEconomicsEngineering

Abstract

fetched live from OpenAlex

Abstract Based on an in‐depth examination of the acquisition, use, maintenance and deterioration of solar home systems in a village in Malaita, Solomon Islands, this article challenges the analytical focus of current debates on electrification in Pacific Island countries – why Pacific Island countries have not yet sufficiently electrified to achieve their development goals. Alternatively it examines what is, how, in this case, rural Solomon Islanders have integrated already available electricity into their daily lives. This perspectival shift highlights how rural Solomon Islanders have developed an energy identity that corresponds to their needs, interests and values, rather than those of national and international actors. It re‐emphasises the struggles of national and international electrification initiatives in rural environments, linking them to a broader distrust in the motivations of external actors. At the same time, it reveals how, throughout their life cycle, rural solar home systems have become integrated into processes of social reproduction rather than development aspirations. Contrary to dominant debates, rural solar home systems matter most in the opportunities that they provide for reciprocal exchange than for what the electricity enables them to do.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.007
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.212
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2020
Admission routes1
Has abstractyes

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