How a price‐support policy can hurt the environment: Empirical evidence from Northeast China
Bibliographic record
Abstract
Abstract During the corn stockpiling system reform in Northeast China between 2008 and 2015, corn production expanded dramatically, and corn residue, which was mostly burned in‐situ, caused severe air pollution issues. Using a difference‐in‐differences approach, we assessed the effects of the corn stockpiling system reform in China and its associated environmental outcomes with a provincial‐level dataset. Our results suggest that the implementation of this policy significantly increased annual corn production in Northeast China by 15.1%. We also observed a substitution pattern between corn and soybean cultivation in the treatment area, with a percentage point increase in the net soybean‐to‐corn profit ratio leading to a decrease in corn production by 0.023 percentage points. Overall, based on changes in crop patterns during the system reform, increased straw resulted in increased burning and the resulting consequence to the environment is a net pollution increase equivalent to 16.03%, 0.33%, and 3.64% of the smoke and dust, SO2, and NOX, respectively, from the industrial sector in the treatment provinces.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".