Does a property‐specific environmental health risk create a “neighborhood” housing price stigma? Arsenic in private well water
Bibliographic record
Abstract
This paper examines the impact of arsenic contamination of groundwater on sale prices of residential properties and bare land transactions in two Maine towns, Buxton and Hollis, that rely on private wells to supply their drinking water. Prompted by tests of well water by the state of Maine, media attention focused on the communities in 1993 and 1994 when 14% of private wells were found to have arsenic concentrations exceeding the U.S. Environmental Protection Agency standard of 0.05 mg/L. Households could mitigate the serious health risks associated with arsenic ingestion by purchasing bottled water or by installing a reverse osmosis home treatment system. Our results indicate that the initial arsenic finding in 1993 led to significant, but temporary, 2 year decreases in property prices. This is a much shorter effect on prices than has been observed for Superfund sites, where prices can be depressed for a decade. These results suggest that a property‐specific contamination incident that is treatable may not have a long‐lasting effect on sale prices, but further research is needed to confirm if the dissipation of the price effect was actually due to the installation of in‐home water treatment systems or due to the dissipation of perceived risk once the media coverage stopped.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".