Climate change as the ‘new’ security threat: implications for Africa
Bibliographic record
Abstract
Once it was an environmental issue, then an energy problem, now climate change is being recast as a security threat. So far, the debate has focused on creating a security ‘hook’, illustrated by anecdote, to invest climate negotiations with a greater sense of urgency. Political momentum behind the idea of climate change as a security threat has progressed quickly, even reaching the United Nations Security Council. This article reviews the linkages between climate change and security in Africa and analyses the role of climate change adaptation policies in future conflict prevention. Africa, with its history of ethnic, resource and interstate conflict, is seen by many as particularly vulnerable to this new type of security threat, despite being the continent least responsible for global greenhouse gas emissions. Projected climatic changes for Africa suggest a future of increasingly scarce water, collapsing agricultural yields, encroaching desert and damaged coastal infrastructure. Such impacts, should they occur, would undermine the ‘carrying capacity’ of large parts of Africa, causing destabilizing population movements and raising tensions over dwindling strategic resources. In such cases, climate change could be a factor that tips fragile states into socio-economic and political collapse. Climate change is only one of many security, environmental and developmental challenges facing Africa. Its impacts will be magnified or moderated by underlying conditions of governance, poverty and resource management, as well as the nature of climate change impacts at local and regional levels. Adaptation policies and programmes, if implemented quickly and at multiple scales, could help avert climate change and other environmental stresses becoming triggers for conflict. But, adaptation must take into account existing social, political and economic tensions and avoid exacerbating them.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".