Regional Cooperative Disaster Risk Management in Central Asian Borderlands
Bibliographic record
Abstract
This paper examines regional cooperation in disaster risk management (DRM) in the transboundary regions of five Central Asian states: Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan. Regional cooperation to reduce disaster potential is a rather recent endeavour both internationally and in the region. Cooperation to enhance environmental security in post-Soviet Central Asia is slowly strengthening monitoring, planning, and prevention of natural disasters with a new approach that anticipates risks and hazards and seeks to reduce the likelihood of disasters instead of responding to the aftermath. Empowerment of regional associations to coordinate states’ activities to understand and solve common problems is needed. The legacy of the Soviet past and the contemporary states’ efforts to participate in regional cooperative organizations are reviewed and the prospects for new instruments for DRM cooperation are discussed. The needs are multifaceted and complex, but there are glimmers of promise for regional and borderland cooperation.
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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 | 0.000 |
| 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 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".