Bibliographic record
Abstract
Biofuels or energy derived from plant matter has been grabbing attention of the world due to rising oil prices and urgent need to reduce emissions. This has made biofuels a hot legislative and policy making topic for most nation states of the world. In order to ensure that socio-economic and environmental sustainability issues are taken into account during production and use of biofuels, there is a need for suitable regulatory and legal frameworks. This study looks at the development of biofuel legislation, policies and institutions in three case studies, Brazil, United States of America and Canada. As world leaders in production and consumption Brazil and the United States of America have a huge body of legislation dealing with various aspects of biofuel production and consumption. Canada on the other hand has recently begun looking at biofuels as an alternate source of energy and an industry on its own right and is in its infancy in terms of biofuel legislation. This study looks at some salient legislation and bodies which regulate biofuel in these three countries aimed at sustainable development of this sector. Interesting programs to develop cellulosic biofuels and remove the burden from food crops and environmental programs have also been mentioned. This study ends with a comparison of biofuel strategy in the three cases and recommendations for development of future biofuel legislation and regulation.All the relevant literature reviewed was from academic and technical publications – magazines and journals – regarding biofuel/bioenergy regulations and legislation. e.g. UNEP publications on bioenergy and also papers published in international and national conferences on biofuel/bioenergy law and policy were sources of relevant literature. The increased competition over agricultural crops for bioenergy purposes instead of food production has been highlighted as a concern for food security. Competition over the use of land and water resources for bioenergy production and for agricultural purposes increases pressures on these resources at a time where global water reserves are dwindling and potentially greater effect are feared on indigenous and local communities and small-holder farmers. All countries that have or are planning to develop a biofuel industry need to pay attention to these issues while forming biofuel legislation.Governments see the potential for multiple benefits from domestic biofuel production programs. In addition to invigorating rural economies and increasing energy security by reducing imported oil, efficient biofuel production could contribute to goals for reducing green house gas emissions. This would also support development of the rural economy especially small scale farms producing cellulosic feedstock.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".