Contamination by the Israeli military industry and its impact on apartment sale prices in an adjacent Tel Aviv neighborhood: a hedonic pricing model study
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
A window of opportunity opened to investigate present effects of past environmental policies of the Israel Defense Forces and its military industry when one of its facilities, Taas Magen, was required to close down in 1997. For decades, untreated discharge was released into absorption pits, which contaminated the soil and groundwater with many toxic compounds, including the carcinogen trichloroethylene. Surrounding the industrial facility is a housing market, consisting of more than 11,000 apartments, directly affected by the contamination.\n\nThis hedonic pricing model study quantifies the effect of the environmental degradation due to the operations of Taas Magen on the nearby housing market. This was achieved by examining the effect distance away from Taas had on apartment sale prices. Results show that apartments near the facility were more negatively impacted than those further away. Next, the model was expanded to isolate the impact of the contamination from that of the facility by incorporating information regarding the public’s awareness of the degradation. The resulting regression coefficients suggest that only after public acknowledgement of the harm did distance significantly impact prices. Therefore, it is the environmental contamination and not necessarily the facility that negatively impacted prices.\n\nAs a result of the contamination, the mean apartment price loss was -$24,650.74 (’06 dollars), which is approximately 14% of an apartment’s average value. Losses to the surrounding housing market are estimated at $267 to $287 million. These are only a minimum of the total social and economic costs incurred by the greater community, which are estimated to total at least $358 million.\n\nAssuming the government were to fund the estimated $33 million cleanup costs, a minute gain of 1.5% in the value of this $2.2 billion housing market would create the necessary economic benefit to offset the cost of decontaminating the site. Similarly, a more technologically advanced, yet expensive, iron nanoparticle remediation process would require a gain of 10.1% to offset its costs. Such market gains are not unreasonable given a drastic decrease in environmental harms. Furthermore, reclaiming a lost aquifer, reduction in human health risks, restoration of environmental integrity, and further increases to the housing market are all benefits of remediation that may greatly overshadow the concomitant cleanup costs.\n\nFuture research should focus on quantifying all these benefits. With such information at hand, it will undoubtedly become apparent that remediation is socially and economically feasible.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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