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Record W2023118671 · doi:10.1080/15567240600814896

Analyzing Sustainability of Community-based Energy Technologies

2007· article· en· W2023118671 on OpenAlex
M. I. Khan, A. Chhetri, M. R. Islam

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy Sources Part B Economics Planning and Policy · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSustainabilityEnvironmental economicsEnvironmental resource managementCitizen journalismSocial sustainabilityEnergy (signal processing)BusinessRenewable energySustainable developmentSustainability organizationsEnvironmental planningNatural resource economicsComputer scienceEngineeringEconomicsPolitical scienceEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

Abstract Contemporary society has become dependent on energy sources for its continued development and very existence. At the same time, it is becoming increasingly clear that energy development and management techniques are unsustainable given current practices. This paper evaluates the sustainability status of community-based energy technologies. Sustainability assessments usually focus on the immediate impacts of technology. This paper introduces a new methodology to posit a broader definition of true sustainability by examining a time-tested criterion, as well as environmental, economic, and social variants, to assess the sustainability of participatory energy development techniques. This research shows that community-based energy technologies, especially biodiesel and direct solar energy, are sustainable, considering their time-tested functionality and ecological, economic, and societal considerations.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.840

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 studies0.0000.001
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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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