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Record W4387774531 · doi:10.1177/14771535231203564

Comparison of questionnaire items for discomfort glare studies in daylit spaces

2023· article· en· W4387774531 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLighting Research & Technology · 2023
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
FundersSingapore University of Technology and DesignHospital for Sick ChildrenSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsGLAREQuestionnaireConstruct (python library)Reliability (semiconductor)Construct validityPsychologyApplied psychologyComputer scienceMathematicsStatisticsPsychometricsClinical psychology

Abstract

fetched live from OpenAlex

When studying discomfort glare, researchers tend to rely on a single questionnaire item to obtain user evaluations. It is unclear whether the choice of questionnaire item affects the distribution of user responses and leads to inconsistencies between studies. This study aims to investigate if different glare questionnaire items yield similar distributions of user discomfort in daylit environments. We conducted a comparative study of selected questionnaire items from previous glare experiments, testing them in three independent user studies with different lighting conditions and glare stimuli. We compared the resulting outputs across questionnaire items with 540 data points from 149 participants. Results indicated that ordinal questionnaire outputs show strong correlations (0.68 < ρ < 0.85), high internal reliability (α = 0.93) and captured the same latent construct. Binary questionnaire items reflected different glare thresholds but still correlated well with ordinal items. The construct validity of tested questionnaire items was confirmed through responses to an open-ended question. These findings suggest that the tested questionnaire items may be used for category rating-type discomfort glare evaluations and consistently capture the same construct.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.146
GPT teacher head0.463
Teacher spread0.318 · 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