The Impact of Charcoal Production on the forest of Sub-Saharan Africa: A theoretical Investigation
Bibliographic record
Abstract
This paper examines the sustainability of charcoal production that maximizes social welfare based on optimal control techniques visa-vis the activities of profit maximizing charcoal producing firms in South Sahara Africa. I set up a theoretical model involving the socially optimal charcoal production that will maximize the socially optimal discounted sum of net benefit of Charcoal production for both the private profit maximization firm and that which will yield sustainability. After solving for the optimal choices for both functions it reveals that there is indeed divergence between these two entities simply because environmental degradation and deforestation (externalities) associated with charcoal production are not internalized into the production function of the profit maximizing charcoal producing firms. These externalities would lead to unsustainability of the forest environment and subsequently deforestation. Fiscal policy measures and public ownerships are recommended to deal with externalities that are inherent in charcoal production so as to improve sustainability while ensuring charcoal continues to provide livelihood benefits for the numerous people that live in the charcoal producing belt.
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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 | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".