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Record W2071625788 · doi:10.1108/lhtn-07-2014-0059

Environmental sustainability and libraries: facilitating user awareness

2014· article· en· W2071625788 on OpenAlexafffundabout
Andrea K. Townsend

Bibliographic record

VenueLibrary Hi Tech News · 2014
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsUniversity of Alberta
FundersVictoria UniversityUniversity of AlbertaUniversity of Victoria
KeywordsCertificationSustainabilityLeverage (statistics)OriginalityBusinessVariety (cybernetics)Knowledge managementWorld Wide WebComputer sciencePolitical scienceCreativity

Abstract

fetched live from OpenAlex

Purpose – The purpose of this research paper is to examine how Canadian Leadership in Energy and Environmental Design (LEED)-certified libraries are facilitating awareness about environmental sustainability to library users. Design/methodology/approach – Twenty-four Canadian LEED-certified libraries were surveyed regarding internal initiatives, and methods used to promote their certification and green building features to library users. Findings – The research found that the majority of Canadian LEED-certified libraries were incorporating a variety of internal initiatives and methods to highlight their LEED-certification to library users. The findings show the majority of these libraries were actively involved in creating awareness about this topic to library users. Originality/value – This research may provide valuable information for libraries wanting to incorporate initiatives that bring awareness to environmental sustainability, or for libraries wanting to use existing green building features to help leverage awareness and learning about this topic.

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)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.139
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.005
Scholarly communication0.0110.007
Open science0.0010.010
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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 designNot applicable
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

Citations18
Published2014
Admission routes3
Has abstractyes

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