Surface Coal Mining and Human Health: Evidence from West Virginia
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
This article presents the first panel‐data evidence of a human health externality from the air pollution generated by surface coal mining. In West Virginia, a standard deviation increase in a county's exposure to surface coal mining is associated with 9.85 more asthma hospitalizations per 100,000 residents in a given quarter. Interpreted causally, this suggests over $11 million in hospitalization costs over the 6‐year study period. The study builds on earlier cross‐sectional research by controlling for unobserved county‐level heterogeneity, and by defining more accurate measures of exposure. Both methods are shown to reduce the bias associated with earlier estimates of coal mining's effect on health. Young and elderly women demonstrate the largest sensitivities to surface mining. Falsification tests reveal that neither hernias nor bone fractures demonstrate any relationship with surface mining activity.
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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it