Application of the Von Thünen Model in Determining Optimal Locations to Transport Compost for Crop Production Outside of Yaoundé, Cameroon
Bibliographic record
Abstract
This research developed and applied a non-linear von Thunen model to explore and determine optimal and profitable distances for transporting compost from the city-centre of Yaounde, Cameroon to surrounding farm areas. Baseline model results indicate that Yaounde’s annual compost production (124,320 tons) is only profitable for farms located within a 79 km radius of the city. Those farms located within a 79 km (or less) radius of the city can be characterized as “beneficial farming zones”; they enjoy significant profits and have a positive shadow price value from the use of compost. However, farms located within an 80-400 km radius of the city incur losses and a compost shadow price that approaches zero. The losses of the latter farms indicate that it is not profitable to use compost for crop production beyond this radius range. As compost production increases and more of it is made available to farmers, the shadow price of the compost decreases. A lower shadow price translates into higher farm profits because lower costs are incurred for crop fertilization. Farms located at distances of 80 km, 70 km, 60 km, 50 km, and 45 km from the city-centre will attain a zero shadow price when compost availability increases by 25%, 50%, 75%, and 100%, respectively. Therefore, it is recommended that the city of Yaounde amends its politics to help increase compost shipments to those farmers located farthest from the city-centre, so that these farmers may lower their overhead costs and increase their overall farm profits. Appropriate state actions could include appropriating funds for roads and transportation infrastructure, as well as encouraging the formation of farm cooperatives in order to transport bulk shipments of compost at lower rates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".