Air pollution exposure and its impacts on everyday life and livelihoods of vulnerable urban populations in South Asia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Urban populations in South Asia are regularly exposed to poor air quality, especially elevated concentrations of fine particulate matter (PM 2.5 ). However, the potential differential burden for the urban poor has received little attention. Here, we evaluate the links between occupation, patterns of exposure to PM 2.5 , and the impacts at an individual and household level for vulnerable populations in Lahore (Pakistan), Kathmandu (Nepal), and Mandalay (Myanmar). We conduct personal exposure measurements and detailed interviews, identifying a wide range of impacts at individual and household levels. Low-income populations are concentrated in occupations that expose them to higher concentrations. Individuals report a range of adverse health impacts and limited capacities to reduce exposure. The lost income, compounded with the costs of managing these health impacts and limited opportunities for alternative employment, can deepen the socioeconomic vulnerability for the household. Reducing these risks requires targeted interventions such as improved social safety nets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 it