Inequality of Low Air Quality-Related Health Impacts among Socioeconomic Groups in the World of Work
Bibliographic record
Abstract
This research aimed to assess the perceptions of air quality and health symptoms caused by low urban air quality among vulnerable socio-economic groups in the world of work in Bangkok, Thailand through a questionnaire survey of 400 workers of both formal and informal sectors in the five districts with different socio-economic characteristics and levels of air pollution. The findings showed symmetry between air quality-monitoring data and health symptoms of different socio-economic groups but asymmetry between air quality-monitoring data and people's perceptions of air quality in their areas. It also showed inequalities of low air quality-related health impacts on socio-economic groups in the world of work. People working near the streets, highways, and industrial zones tended to have more health symptoms related to low air quality, and informal sector workers faced more health risks than formal sector workers. The study appeals for effective air pollution communication to enhance the public and informal sector worker population's literacy of air pollution, the sources of air pollution and its critical health impacts, and the available and sufficient primary care organizations and community health care centers to address work-related health needs to reach the informal sector worker population.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".