Climate Change, Environment and Armed Conflicts in Nigeria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Climate change has become a major cause of conflicts in Nigeria, which directly causes multiple forms of insecurity in the country. In different parts of the globe, it manifests as earth quake, hurricane, tsunami, etc. Nigeria has received its share of climate change both in two opposite forms. In the southern coastal states of Lagos, Bayelsa, and Rivers State, the ocean and overflowing waters continually threatens to wipe away the people. However, this study focuses on the north and parts of southern Nigeria, where the impact of climate change has generated armed conflict. The study which used qualitative methodology traced how climate change and the emergence of drought, famine and other forms of environmental changes leads to resource competition over land, mineral resource, water ways and by extension generating armed conflicts in many parts of Nigeria. It found that climate change caused mass migration and the settler versus non-settler conflicts that manifested in different as herdsmen-farmer conflict, as well as the armed conflict among the Ezza and her neighbours and also contributed to the Ife-Modakeke crisis in the country. Finally, the study documents multi-dimensional road-map to environmental peace and adaptations for sustainable societal development.
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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 it