MétaCan
Menu
Back to cohort
Record W2098460332 · doi:10.1177/0013916511420560

Linking Lighting Appraisals to Work Behaviors

2011· article· en· W2098460332 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironment and Behavior · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsNational Research Council Canada
FundersNational Research Council CanadaPublic Works and Government Services CanadaTechnische Universiteit Eindhoven
KeywordsStructural equation modelingMoodPsychologyWork (physics)Work engagementApplied psychologyConceptual modelSocial psychologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Among those concerned with practical matters of office design, demonstrations that the work environment affects employees’ well-being and work behaviors are thought to be important to support client decision making. Veitch, Newsham, Boyce, and Jones developed a conceptual model in which lighting appraisal and visual capabilities predicted aesthetic judgments, mood, and performance. This article extends that model to include measures of work engagement, using experimental data originally reported by Newsham, Veitch, Arsenault, and Duval. Structural equation modeling showed strong fit to a model in which lighting appraisals indirectly influenced work engagement through aesthetic judgments and mood. This evidence that providing a satisfactory work environment can contribute to employee effectiveness merits further study by environmental and organizational psychologists.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0050.002

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 head0.033
GPT teacher head0.251
Teacher spread0.218 · 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