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Record W2154170520 · doi:10.1108/14676370610639227

Energy service companies as a component of a comprehensive university sustainability strategy

2006· article· en· W2154170520 on OpenAlexaff
Joshua M. Pearce

Bibliographic record

VenueInternational Journal of Sustainability in Higher Education · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsWestern University
Fundersnot available
KeywordsSustainabilityEnvironmental stewardshipEnvironmental economicsBusinessStewardship (theology)Context (archaeology)Service (business)Efficient energy useEcological footprintEnvironmental resource managementEconomicsMarketingEngineering

Abstract

fetched live from OpenAlex

Purpose This paper aims to quantify and critically analyze the best practices of a comprehensive environmental stewardship strategy (ESS), which included a guaranteed energy savings program (GESP) that utilized an energy service company (ESCO). Design/methodology/approach The environmental and economic benefits and limitations of an approach utilizing an ESCO are critically analyzed in the context of implementing a comprehensive university sustainability strategy. Findings A GESP, which utilized the technical and financial expertise of energy service companies, improved the operational efficiency, decreased the ecological footprint, and reduced the operating costs of the university. Practical implications Energy‐saving projects are “win‐win” situations, addressing both economy and ecology. Utilizing energy service companies in the university setting is a useful method to catalyze university administration to support sustainability initiatives and accelerate the implementation of comprehensive sustainability strategies. Originality/value The current waste rampant at most universities provides a large number of opportunities to improve environmental stewardship while reducing operating costs. This paper provides a new model utilizing energy service companies to capitalize on these opportunities to move universities towards sustainability.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.021
GPT teacher head0.337
Teacher spread0.316 · 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

Citations2
Published2006
Admission routes1
Has abstractyes

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