Biofuel Policy as a Key Driver for Sustainable Development in the Biofuel Sector: The Missing Ingredient in Zimbabwe’s Biofuel Pursuit
Bibliographic record
Abstract
As global warming continues to be a challenge, there is urgency to look into fossil fuel alternatives for sustainable energy supplies which have also been hastened by the volatility of crude oil prices and the fact that fossil fuel depletion is clearly in sight. Zimbabwe has not been spared of the negative effects of climate change which have affected both the food and energy sectors. This has proved to be a major challenge for the sustainable development of the country’s economy. In an effort to be energy independent, the country has for over decades looked into the prospect of utilising its vast biomass resources to produce biofuels. These programmes have been met with a number of challenges which has seen most such projects not succeeding. The current paper gives a narration of the history of biofuel programmes in Zimbabwe looking at their driving factors and reasons that led to their collapses. Lack of a national biofuel policy is identified as the major factor that has been the missing link in the past and must be addressed. The paper goes further to call for the crafting of a National Biofuel Policy for Zimbabwe highlighting the major thematic issues it would need to cover. An implementation plan for the programme has been proposed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".