A Three-Dimensional Evaluation Model of National Fragility Based on Dynamic Weighting
Why this work is in the frame
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Bibliographic record
Abstract
Nowadays, climate change has become an increasingly important factor that influences the national development. In this paper, we propose the three-dimensional model based on dynamic weighting to measure national fragility, while taking into account a series of climatic factors like temperature, rainfall et al. Our model includes 20 indicators which can be divided into economic factors, social factors and environmental factors. We first divided all indicators into cost-type, benefit-type and moderate indicators, and normalized them based on different types of indicators. Then, combining modified entropy weight method and AHP, the weights of 20 indicators and three factors in the evaluation model are defined. In the three-dimensional evaluation model, we use the length of the evaluation curve to evaluate the national fragility and measure the balance of the three factors with the angle between the curve and the diagonal of the model. Moreover, since countries at different stages of development have different development focuses, we have developed an "S-type" function to dynamically measure the different emphasis on the degree of national fragility and the balance of the three evaluation factors. Then, we calculate the comprehensive fragility index by giving different weights for the degree of national fragility and the balance of the three factors. Finally, we use two different countries which are China and Sudan to verify the rationality of the model. The results show that our model can reasonably measure the fragility of countries in different development levels, which also proves its adaptability and practicability.
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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 | 0.004 | 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) | 0.001 | 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