The Socio-economic and Environmental Implications of Supplying Charcoal in Yaounde City
Bibliographic record
Abstract
This article aims to identify and assess the socio-economic and environmental implications of supplying charcoal in the city of Yaounde. To achieve the above-mentioned goal, investigations based on a standardized questionnaire (130 charcoal producers and sellers), formal interviews (7 resource persons), informal discussions, field observations and floristic survey were carried out in Bikok between the last quarter of 2016 and the second quarter of 2017. Bikok, a subdivision located in the neighbourhood of Yaounde is one of the most important supply sites of charcoal for the city. Investigations revealed that, accelerated demographic growth over the past fifty years, unemployment and poverty constitute the main factors for the increase in the production and consumption of charcoal in the city. Poverty, unemployment and the urge for the satisfaction of basic needs constituted the main reasons for involvement of 98.8% of charcoal producers in the activity. The increase in urban demand for charcoal is at the origin of several significant biophysical impacts, including the degradation of forests and soils as well as the decrease in the availability of some Non-Timber Forest Products and animal species. In the survey villages, a total area of 3.1 hectares of forest is cut each year and the average distances from inhabited areas to harvesting areas, increased from 0.8 to 5 km in 10 years. 76.6% of charcoal producers believe that some animal species are increasingly rare in the locality. On the socio-economic level, this activity creates jobs, generates income thereby increasing the living standards of producers and sellers. More than 300 people are involved in this activity who earns on average an income of 3000 to 6000 Central African Franc (XAF) per day. Decrease in the availability of certain NTFPs and damage to the health of producers constituted some of the negative socio-economic impacts of this activity. It is imperative to adopt measures to limit the negative impacts of this activity while ensuring a sustainable supply of charcoal in the city or the use of alternative sources of fuel.
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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 | 0.001 |
| 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".