Disasters in ‘development’ contexts: Contradictions and options for a preventive approach
Bibliographic record
Abstract
The relations of development and disaster offer a starting point for an overview of disaster risk reduction (DRR) in African contexts. A social vulnerability approach is adopted with its goal of improving conditions for persons and places most at risk. However, this approach faces serious contradictions in both the disasters and development scenes. Disaster events and losses have grown exponentially in recent decades. So have advances in disaster-related knowledge and the institutions and material resources devoted to disaster management. Evidently, the latter have not reduced disaster incidence or over all losses. Similar contradictions appear in development. By some measures, in most developing countries the economy has grown much faster than population. Yet, indebtedness, unemployment and insecurity seem worse in many countries. Poverty, the avowed target, remains huge in urban, peri-urban and rural areas singled out by disaster losses. Problems also arise from separate treatment of development and disaster. Climate change and the global financial crises challenge some of the most basic assumptions. The promise of ‘developed nations’, built around massive use of fossil fuels, puts global and African economic growth on a collision course with environmental calamity. The 2008 financial crisis has undermined the safety of global majorities, as well as reliance on development assistance. The case for alternatives in development and DRR is reinforced, including the vulnerability-reducing responses highlighted in the Hyogo framework for action. However, this is being undermined by a return to a civil defence-type approach, an increasingly militarised, and for-profit, focus on emergency management.
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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 | 0.001 |
| 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".