Historical Analysis of the Role of Governance Systems in the Sustainable Development of Biofuels in Brazil and the United States of America (USA)
Bibliographic record
Abstract
The United States of America and Brazil are the world’s first and second-largest biofuels producers. The United States (U.S.) has dedicated a significant portion of agricultural land for crops to produce biodiesel, while Brazil has been using sugar cane as raw material to produce ethanol. To make the world’s top producers in global biofuel markets, various institutions in each country have played significant roles. These institutions include renewable energy legislators, bioenergy policymakers, and energy ministries of their governments. This study delineates the historical role of these institutions responsible for the sustainable development of biofuel industries in both countries. It also provides an overview of economic impacts as a result of institutional decisions. The study reveals that systematic legislations and sustainable and robust renewable energy policies of government institutions have helped the U.S. and Brazil to boost their bio-economies. As both countries intend to keep expanding their biofuel productions, the role of key government institutions is vital in the sustainability of biofuels.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".