Impact of United States Corn-Based Ethanol Production on Land Use
Bibliographic record
Abstract
This study measures the impact of corn-based ethanol production in the United States on land use in other countries, or indirect land use. Indirect land use is a change from non-cropland to cropland (e.g. deforestation) that may occur in response to increasing scarcity of cropland. As farmers worldwide respond to higher crop prices in order to maintain the global food supply and demand balance, pristine lands are cleared and converted to new cropland to replace the crops for feed and food that were diverted elsewhere to biofuel production. The results show that increasing ethanol production in the US has a positive and significant relation to U.S corn price. However, U.S. corn price does not have a significant impact on changes in corn acreage in Brazil and other countries such as Canada, Japan and China. Although many authors have hypothesized that increased ethanol production in the U.S. will increase corn prices, which will result in increased change in land use in other countries, these results suggest that the effect is minimal at best. This is important because although production of ethanol for fuel is often criticized for negatively impacting the environment because of indirect land use, this study was unable to prove the existence of indirect land use.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".