Differences in teachers’ satisfaction with indoor environmental quality and their well-being in new, renovated and non-renovated schools
Bibliographic record
Abstract
Most studies on buildings’ renovations in relation to indoor environmental quality (IEQ) and occupants’ well-being have focused on offices, while those investigating schools focused on students rather than teachers. Most of these studies limited their assessment of well-being to occupants’ satisfaction with IEQ factors, overlooking essential aspects related to psychological, social and physical well-being. This article presents results of a research conducted in 32 schools in Manitoba, Canada, to assess teachers’ IEQ satisfaction and well-being in new, renovated and non-renovated schools. The research involved adapting and refining an IEQ satisfaction survey and developing and refining three new surveys to assess teachers’ psychological, social and physical well-being. The results of the refined surveys showed statistically significant differences in teachers’ satisfaction with IEQ factors between the new and renovated schools on one hand and the non-renovated ones on the other. However, no statistically significant differences were found in teachers’ psychological, social and physical well-being perceptions between all pairs of the three school categories analysed. Association analyses suggested a potential indirect impact of schools’ renovations on teachers’ well-being via their satisfaction with IEQ. The results of this study should aid school managers in making strategic decisions about the maintenance of their existing schools.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".