Case study: A survey of perceived noise in Canadian multi-unit residential buildings to study long-term implications for widespread teleworking
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
Trends of urbanization, densification, and telework all point to increasing exposure to ambient noise for workers. With the lockdown policies implemented in response to COVID-19, a research opportunity to study perceived noise exposure for teleworking arose. This paper presents the results of a survey on noise issues in multi-unit residential buildings (MURBs) and the consequent effects on occupants' well-being and productivity during the lockdown. Responses were collected from 471 MURB occupants across Canada. The results show that, despite the decrease in environmental noise, many are annoyed by outdoor noise, particularly from traffic and construction activities, and indicated that it affects their ability to work. Effects on ability to work from home were more frequently reported for indoor noise sources particularly airborne and impact noises coming from neighboring suites. Our findings, however, show that noise coming from occupants in the same suite (i.e. roommates and family) present the biggest issue. The findings indicate that existing noise conditions in MURBs might not be suitable for a permanent large-scale implementation of teleworking.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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