AN EVALUATION OF INDOOR ENVIRONMENTAL QUALITY AND OCCUPANT WELL-BEING IN MANITOBA SCHOOL BUILDINGS
Bibliographic record
Abstract
ABSTRACT This exploratory research aims to evaluate indoor environmental quality in the classrooms of three school buildings in Southern Manitoba, Canada, and to evaluate the well-being of these schools' teachers as it pertains to their perception of their classrooms' indoor environment. The schools include a middle-aged, conventional school; a new, non-green school; and a new, green school certified using the Leadership in Energy and Environmental Design rating system. The methodology involved using a mobile instrument cart to conduct snapshot measurements of thermal comfort, indoor air quality, lighting and acoustics in classrooms and an occupant survey to evaluate teachers' long-term satisfaction with their classrooms' indoor environmental quality. The results showed that the new, green and new, non-green schools' classrooms performed better than the conventional, middle-aged school's classrooms with respect to some aspects of thermal comfort and indoor air quality only. Teachers in the new, green school and in the new, non-green school were more satisfied than teachers in the conventional, middle-aged school with their classrooms' overall indoor environmental quality, lighting quality and indoor air quality. Surprisingly, the new, green and new-non green school classrooms' performance were very comparable with the new, green school's classrooms performing statistically significantly better with respect to relative humidity. Similarly, none of the differences in teachers' satisfaction ratings between the new, green and new, non-green school were statistically significant.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".