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Record W4252487730 · doi:10.1121/1.4970238

Subjective acoustical quality in healthcare office facilities

2016· article· en· W4252487730 on OpenAlexaff
Murray Hodgson

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2016
Typearticle
Languageen
FieldPsychology
TopicFacilities and Workplace Management
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsOpen planJob satisfactionHealth careRoom acousticsApplied psychologyFacility managementPerceptionProductivityQuality (philosophy)PsychologyAcousticsBusinessEngineeringMarketingSocial psychologyCivil engineering

Abstract

fetched live from OpenAlex

Health-care facilities include many non-clinical office spaces for administrative staff; the role of acoustics in these spaces has been underexplored. This paper discusses the acoustical part of a study of indoor environmental quality (IEQ) in 17 healthcare office facilities. A subjective survey assessed office worker perceptions of their environments in general, and satisfaction with the acoustics. Self-reported productivity, well-being, and health outcomes were also captured. Satisfaction was lower with acoustics than with other aspects of IEQ. Satisfaction results were related to room type (e.g., open plan vs. shared vs. private office) and the absence or presence of a sound-masking system. Acoustics was the most important aspect of IEQ in predicting occupant satisfaction and well-being. Regression models were developed to predict workplace satisfaction, well-being, and job satisfaction from survey responses. Results of physical acoustical measurements showed very low correlations with subjective responses. The knowledge gained from this study informs the decision-making of designers and facilities management for upgrades and future design projects.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.316
Teacher spread0.290 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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