Developing Disaster: Power, Structural Violence, Insurance-Linked Securities, and the International Political Economy of the Disaster Politics Nexus
Bibliographic record
Abstract
Abstract This article presents an alternative framing of disasters as a form of structural violence resulting from the unequal distribution of structural power between various groups, organizations, institutions, and states in the contemporary global political economy. The article utilizes a theoretical framework that combines Johan Galtung’s typology of violence and Susan Strange’s conceptualization of structural power to open up new space for analysis in the disaster politics nexus. The article applies its framework to explore how an understanding of disasters as a form of violence problematizes trends within mainstream disaster risk reduction (DRR) policies. Specifically, the article examines the integration of financial risk-sharing mechanisms into the disaster politics nexus through new public–private partnerships between insurance and reinsurance firms, international financial institutions, and governments to transfer catastrophic risk to global capital markets. The article seeks to repoliticize these changes and bring questions of power back into the larger conversation surrounding DRR policies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".