From drought to displacement: Assessing the impacts of climate change on conflict and forced migration in West Africa's Sahel Region
Bibliographic record
Abstract
Across Africa's semiarid Sahel region, temperatures have risen faster than the global average, resulting in severe threats to water access, food security, and human health. Key climate factors such as desertification interact with ethnic and economic tensions, exacerbating violence between pastoral and farming groups competing over degraded productive land and water resources. Mounting climate pressures act as threat multipliers for both violent conflict and internal displacement across countries spanning Senegal to Sudan. This perspective examines intersections of climate change, violent clashes, and forced migration using incidents in Nigeria and Burkina Faso-where droughts, floods and agricultural losses continue to worsen. With 8 million internally displaced persons in the region now, urban areas face overburdened infrastructure while attempting to host influxes of traumatized, impoverished migrants facing further risks. This article argues that integrated policy action is urgently needed to mitigate climate change, enhance community resilience, and protect vulnerable groups to ease cascading humanitarian crises and achieve development goals amid spiraling environmental pressures across West Africa.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".