An overview of indoor environmental conditions in work-from-home settings
Bibliographic record
Abstract
During the last week of March 2020, about 4.7 million workers in Canada transitioned to working from home due to the pandemic. A similar transition occurred at a global scale. Few studies have evaluated the WFH setting from a perspective that’s been a significant public concern during the COVID-19 pandemic: indoor environmental quality (IEQ). The objective of this paper is to present an analysis of the IEQ conditions in WFH settings based on a field study of 95 WFH sites during May-July 2022 in the Pacific Northwest region. The IEQ variables of air temperature, relative humidity, CO2, total volatile organic compounds, PM2.5, ambient light and noise were measured continuously at 10-minute intervals for the duration of the study. A preliminary analysis of the IEQ data shows the indoor air temperature in WFH settings within the study sample, ranged between 15.7-32°C, with a mean value of 22.7°C (SD = 2.3°C). The mean indoor concentrations of CO2, TVOCs and PM2.5 were 674 ppm (SD = 324 ppm), 288 ppb (SD = 515 ppb) and 4.7 μ/m3 (SD = 20.5 μ/m3) respectively. The mean values for relative humidity, light and noise were 53% (SD = 7%), 174 lux (SD = 349 lux) and 53 dB (SD = 5 dB). Associations between type of residence and most of the IEQ variables were found.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".