Proximity to Combined Sewer Overflow-Impacted Waters in Philadelphia: A Geographic Information Systems Study to Explore Environmental Injustice
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
Background: Recreating in waterbodies impacted by combined sewer overflows (CSOs) can present health risks due to exposure to microbial pathogens. This study compares population characteristics of those living within walking distance to CSO-impacted versus nonimpacted waters in Philadelphia to determine whether these populations differ by race, ethnicity, and sociodemographic characteristics. Methods: Adults recreating at or near natural water bodies in Philadelphia completed a questionnaire that assessed the average walking distance to each site. Walking distance boundaries informed by questionnaire responses were created around each waterbody in Philadelphia, and population-level census data corresponding with block groups included within each buffer were used to characterize those living near a CSO-impacted and nonimpacted waterbodies in Philadelphia. Results: Compared with populations residing in census block groups within walking distance to a nonimpacted waterway, populations living within the same distance to a CSO-impacted waterway were more likely to comprise Hispanic residents (standardized adjusted prevalence ratio [APR] = 1.13) and those living in poverty (APR = 1.21) and less likely to comprise White residents (APR = 0.76). Conclusion: These findings suggest that communities of color and those experiencing poverty are disproportionally impacted by environmental hazards.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.007 |
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