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Record W2044257353 · doi:10.1080/00038628.2012.667939

Do green offices affect employee engagement and environmental attitudes?

2012· article· en· W2044257353 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArchitectural Science Review · 2012
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEmployee engagementAffect (linguistics)Job satisfactionPsychologyWork engagementProductivityScale (ratio)BusinessWork (physics)Work environmentEnvironmental designMarketingApplied psychologySocial psychologyPublic relationsEngineeringPolitical scienceGeographyEconomicsCivil engineering

Abstract

fetched live from OpenAlex

Employees working in 15 public- and private-sector office buildings in a mid-sized Canadian city reported their level of work engagement (as measured by job satisfaction, perceived productivity and affective organizational commitment), environmental orientation, pro-environmental behaviour and opinions about the physical aspects of their buildings. The buildings’ green attributes were assessed on an objective 36-item scale. Neither engagement nor environmental attitudes were correlated with green design attributes. However, employees’ office impressions were significantly negatively correlated with the number of green design attributes. Surprisingly, the results suggest that green design in office buildings does not have a positive effect on employee engagement or on environmental attitudes and behaviours.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.451

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 studies0.0000.000
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 head0.025
GPT teacher head0.292
Teacher spread0.267 · 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