Kindergarten physical setting guidelines: A review from indoor air quality perspectives
Bibliographic record
Abstract
The kindergarten’s indoor air contained a number of pollutants, including total volatile organic compounds, particulate matter, carbon monoxide and insufficient ventilation with high carbon dioxide levels, which exceeded the indoor air quality (IAQ) guideline. The presence of these pollutants is caused by various factors including inappropriate physical setting. Indisputably, authorities throughout the countries provide guidelines for designing kindergartens' spaces, however it is limited to general explanations and only guided by early education compliance. It is vital to determine which kindergarten regulations may contribute to poor IAQ. This paper explores national kindergarten physical setting guidelines and how it affects IAQ. A document analysis method was used to determine the characteristics and differences between kindergarten guidelines. Firstly, the composition of each kindergarten guideline was itemised. Then, the study was conducted by making comparisons of the identified items. All the criteria were further reviewed from IAQ perspectives. This study was conducted on guidelines in Australia, Canada, the United States, Singapore and Malaysia. There are five physical setting requirements that influence IAQ : minimum indoor space required per child, sleep area, kitchen and food preparation area, ventilation requirements and furniture and finishes. All activities happen in this microenvironment contribute to IAQ, which is also affected by the ventilation system, furniture and finishes selection. It can be concluded that there is still room for improvement in existing guidelines by taking into account the indoor air perspective. Aside from the main function of kindergarten to provide education, the physical setting of kindergarten also plays a significant role in the growth and health of chidren.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".