The effect of sound masking on employees' acoustic comfort and performance in open-plan offices in Canada
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.
Bibliographic record
Abstract
Sound masking systems are commonly used in open-plan offices to generate a controlled minimum level of background sound, in order to decrease the signal-to-noise ratio of intrusive speech and blend out transient office noise. However, a question in the acoustical design of offices is whether the self-generated noise of occupants may alone be sufficient to provide the background sound level conditions necessary to achieve similar levels of speech privacy and acoustic comfort as sound masking systems. This study examines the relationship between occupant-perceived speech privacy and acoustic comfort under three different acoustic scenarios (no masking, controlled 42 dBA, and 47 dBA masking sound levels). The study was conducted pre-COVID-19 in two separate open-plan offices located in Quebec, Canada that at the time were close to full occupancy. Employees completed subjective questionnaires before and after each change in conditions, focusing on how the sound environment impacted their comfort and work performance during the study. Statistical results show that the occupants were significantly more satisfied during the two sound masking conditions in comparison to the no-masking condition, where only the occupant-generated and exterior/mechanical system noise was present as the background sound. Implications for open-plan offices with lower occupancy conditions post-COVID-19 are discussed.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it