Addressing the Impact of Environmental Displacements of Persons in Africa by Operationalizing Sustainable Development Goals and African Agenda 2063
Bibliographic record
Abstract
Internal displacement due to environmental disasters has become a major humanitarian challenge in Africa, disproportionately affecting vulnerable groups such as women, children, and the elderly. Despite efforts like the New Partnership for Africa's Development (NEPAD) and adherence to the Millennium Development Goals (MDGs), the continent continues to face rising environmental challenges, raising questions about whether these displacements result from a failure to heed environmental warnings and whether development should be approached from a home-grown perspective. African Agenda 2063 and the SDGs now include forced displacement as key targets and indicators, emphasizing a comprehensive approach that extends beyond humanitarian aid to focus on development. This paper explores whether an intentional Afrocentric development plan, alongside the operationalization of the SDGs and Agenda 2063, can effectively mitigate environmentally induced internal displacement in Africa.
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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 | 0.001 | 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".