From Sugarcane To Ethanol: The Historical Process That Transformed Brazil Into A Biofuel Superpower
Bibliographic record
Abstract
Brazil is a biofuel superpower and a pioneer in the large-scale production and use of sugarcane ethanol.The country has plans to replace 10 percent of the world's fossil fuels by 2025 with biofuels (Novo et al., 2010).Brazil is also part of a multilateral agreement signed at the Paris Climate Conference (COP-21) in 2015 and has committed to reducing its greenhouse gas (GHG) emissions by 43% until 2030 compared to 2005 levels (Brazilian Government, 2015).The proposal for GHG reductions is mostly based on the increase of biofuels in the Brazilian energy mix.With historical institutionalism as its theoretical framework, this paper looks at how Brazil grew from a sugar exporter into a global ethanol powerhouse.This research's main question looks at the key historical processes and national actors behind ethanol development in Brazil.Analyzing how sugarcane-based fuels evolved is central to understand how past energy transformations have occurred and will offer insights into future energy transformations concerning Brazil's increasing reliance on ethanol.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".