Energy Use in Building in Front of Climate Change: An Analysis of the Adaptation Strategies of Corn Farmers in Benin
Bibliographic record
Abstract
In Benin, maize production is important for food security and rural household incomes. However, it is subject to climatic variations that induce low yields and productivity levels. This innovative study categorizes the energy sources used in its production to identify levers for improving agricultural productivity. A survey of 230 maize growers in the communes of N'Dali, Sinende and Nikki was carried out. Data were collected using structured questionnaires on farming activities and input use, then converted into energy values using energy equivalence coefficients collected in previous studies. The results reveal a high level of awareness among maize growers (97.4%) of the impacts of climate change on maize production. In terms of the amount of energy derived from labor power, mechanical plowing stood out (133.02 MJ/ha), closely followed by animal-drawn plowing (53.04 MJ/ha) and harvesting (45.18 MJ/ha). In terms of inputs, NPK fertilizer stands out with an energy expenditure of 2238.87 MJ/ha, followed by urea with 1172.95 MJ/ha. Although increasing labor power remains the approach most adopted (61%) by growers to maintain the productivity of their farms, the results revealed a predominance of energy from agricultural inputs (94.91% of total energy), underlining the preponderance of inputs in overall energy requirements.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".