A participatory study of indoor environment quality in homes of children and youth in Kanehsatake First Nation
Bibliographic record
Abstract
Indoor air quality is an important determinant for the health of children and youth, but the conditions within Indigenous communities are understudied. We collaborated with Kanehsatake First Nation in Quebec, Canada, to address this gap using a community-based participatory research approach. Levels of key indoor air indicators, including particulate matter (PM 2.5 ), CO 2 , and relative humidity, were measured in 31 randomly selected households between June 2021 and January 2022. Questionnaires were administered remotely to collect information on housing conditions. Excessive humidity was common, with 52% of households having a relative humidity above 55%. The mean PM 2.5 concentration was 21.0 (standard deviation 38.5) µg/m 3 , with higher mean levels observed in smoking compared to non-smoking households (36.1 µg/m 3 and 10.1 µg/m 3 , respectively). The mean CO 2 level in participating households was 881 ppm (standard deviation 256), with 30% ( n = 9) of homes exceeding 1000 ppm. Flooding rates were high, with 55% of households reporting at least one past flood. One-third of houses were inadequately ventilated relative to occupancy, and over one-quarter reported needing major repairs. The results indicate the value and importance of characterizing the indoor environment in First Nations households and the viability of data collection through community-based participatory research in environmental health research.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".