Vulnerability of agricultural areas to climatic risk and effectiveness of risk management policy scheme in Italy
Bibliographic record
Abstract
At the global level, risk management tools are under discussion, in particular in the agricultural sector, in relation to its vulnerability to climatic risk.The main question points refer to the effectiveness of the most common current policy schemes, based on public support to insurances and compensation aids, in relation to the patterns of risk analysis in the context of climate change.Italy has a long tradition of risk management in agriculture because of the heterogeneity of climatic conditions.The present study has been conducted by Council for Agricultural Research and Economics to explore the potential of the current risk management scheme.One of the more relevant aspects studied is the demand for risk management in terms of exposure to disasters of the agricultural areas and their vulnerability.Crossing this analysis with the policy scheme, it is possible to assess its effectiveness in covering climatic risks.The results show that the current system based on economic tools needs a strong integration into a wider framework of risk assessment and policy strategies addressing climate change adaptation, in synergy with other structural and management measures.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".