A Tale of Two Roads: Groundwater Depletion in the North China Plain
Bibliographic record
Abstract
There is a large literature on the role infrastructure plays in economic development, but few papers document the effect of infrastructure on the sustainability of natural resources. We examine the effect of the arrival of two new national highways on ground water levels in a small agricultural county in the North China Plain - a region that produces most of the nation’s food grains. We first develop a conceptual framework to show that farmers located closer to the highways devote more acreage to crops that are water intensive. We then use a unique GIS-referenced dataset of all the 12,160 tube wells in this county to show that highway construction accelerates the drilling of new wells in farms closer to the highway. In addition, there is greater depletion of the groundwater in wells closer to the two highways relative to wells located farther away. Our estimated depletion rates near the two roads are at least 5 times higher relative to mean depletion rates in the North China Plain. We show suggestive evidence that depletion is caused by a switch from subsistence to commercial cropping, and intensification of farming practices closer to the highway. These results suggest that the resource cost of new infrastructure building may be significant and needs to be incorporated in benefit-cost analysis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".