Environmental Impact of the Real Estate Companies Boom in the Central Region, Ouagadougou (Burkina Faso)
Bibliographic record
Abstract
Aims: Impact of the real estate companies’ boom on the environment in the central region of Burkina Faso (Ouagadougou) and solutions to resorb the negative effects of the activity. Study Design: The present study was run via the Problem-In-Context framework along with the Hydro-Quebec environmental assessment design. Place and Duration of Study: The study was conducted in Burkina Faso, for the Environment department of Fada N’Gourma University for twelve months. Methodology: The environmental impact of the project was assessed according to Hydro-Quebec group method by prioritizing the inventory items regarding to their sensitivity. Results: Burkina Faso revised Law No. 034 on agrarian and land reorganization (RAF) on July 2, 2012. This revision allowed the population to be landowners, generating a boom in Real Estate development with the sale of big surfaces of lands by landowners. This boom is not without impacts on the environment. It leads to the destruction of forests, loss of biodiversity, loss of agricultural production areas, threats to green spaces conservation areas, anarchic occupation of lands, etc. by real estate companies and the non-ecological urbanization of the city of Ouagadougou. The anthropogenic and climatic constraints with which Burkina Faso is confronted generate strong pressure on the existing natural resources: soil, fauna, flora, water, etc. Conclusion: The Burkinabe capital is about to engulf all the surrounding municipalities of Komki Ipala, Komsilga, Koubri, Loumbila, Pabré, Saaba and Tanghin-Dassouri. The main ways to reduce the environmental impacts of this real estate boom are the registration of agricultural production and conservation areas and the revision of the RAF in order to remove the right of land owning to the population.
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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 | 0.000 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".