Assessing farmers’ preferences for the future of the Common Agricultural Policy: insights from of a discrete choice experiment in Germany
Bibliographic record
Abstract
This paper analyses the determinants of German farmers’ acceptance of alternative agricultural policy packages. The analysis is based on a discrete choice experiment with 434 farmers from across Germany. The study participants presented with the choice of three different policy packages in each of the seven choice sets for which responses were to be given, plus an option to withdraw from the present agricultural policy. The data was analysed using a random parameter logit model and a latent class estimation to reveal preference heterogeneity among those surveyed. Around two thirds of respondents declared themselves to be in favour of the continuation of direct payments. Less than half of the respondents (40 %) were prepared in principle to accept higher standards in the environment and animal welfare in return for continued direct payments. However, nearly one quarter (23%) of those surveyed wanted direct payments to continue without having to do anything in return. The majority of farmers surveyed were against a state safety net through market intervention. One third of respondents wanted the abolition of the Common Agricultural Policy in its present form, including direct payments.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".