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Record W7053519924

Workstation characteristics and environmental satisfaction in open-plan offices: COPE field findings

2004· article· en· W7053519924 on OpenAlexfundvenueno aff

Bibliographic record

VenueNPARC · 2004
Typearticle
Languageen
FieldEngineering
TopicMagneto-Optical Properties and Applications
Canadian institutionsnot available
FundersPublic Works and Government Services CanadaNatural Resources CanadaSteelcase
KeywordsWorkstationJob satisfactionFlexibility (engineering)Partition (number theory)PerceptionField (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Open-plan offices are notorious for their unpopularity with occupants, but remain popular with organizations because of their flexibility and apparent cost-effectiveness. As part of NRC's Cost-effective Open-Plan Environments project, a field study of 779 workstations in 9 buildings was conducted to examine the relationships between measured physical conditions and occupant satisfaction with those conditions. (Two presentations at CPA 2002 reported on a subset of these data.). Hierarchical multiple regression analyses controlled for age, job type, and gender first; then examined the effects of workstation characteristics on five aspects of satisfaction: satisfaction with privacy and acoustics; satisfaction with lighting; satisfaction with ventilation; overall environmental satisfaction, and job satisfaction. As predicted, increasing workstation size improved satisfaction with privacy. Having access to a window strongly improved satisfaction with lighting. Lower partition heights were associated with higher overall environmental satisfaction and higher job satisfaction. This finding is contrary to previous research and common sense, particularly with respect to privacy; however, it might reflect the desire for better daylight penetration, which lower partitions afford, and the perception that lower partitions improve ventilation.

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)0.000
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 score0.807
Threshold uncertainty score0.334

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)0.0000.000

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 head0.010
GPT teacher head0.199
Teacher spread0.189 · 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 designObservational
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

Citations0
Published2004
Admission routes2
Has abstractyes

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