Agricultural Risk Management in the European Union: A Proposal to Facilitate Precautionary Savings
Bibliographic record
Abstract
Summary Through a series of reforms, the European Union (EU) replaced most of its trade distorting price support programmes with safety net provisions and direct payments decoupled from production. This has resulted in greater market orientation and a situation in which farmers face increased price variability. Policy now emphasises the development of business risk management (BRM) programmes, such as crop and whole farm insurance. However, for various reasons EU‐wide adoption of BRM programmes and farmer uptake and use of risk instruments is below expectations. We recommend the use of farm‐specific savings accounts upon which farmers can draw when revenues fall below a proportion of expected revenue. Farmer‐Directed Precautionary Savings Accounts (FDPSAs) would complement traditional non‐financial, on‐farm risk management strategies and private/public risk transfer strategies. FDPSAs would protect farmers against shallow losses and, along with crop and/or index‐based insurance, also protect against deep losses. Further, this form of protection is easy to understand and administer and leaves complete control with the producer.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.017 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".