Agri-environmental Policy in the
Bibliographic record
Abstract
(CATPRN). The CATPRN is funded by Agriculture and Agri-Food Canada but the views expressed in this paper are those of the authors and should not be attributed to the funding agency. The EU has argued that some agricultural subsidies are needed to provide the optimal amount of externalities (both positive and negative) produced by agriculture. The argument is that agriculture is “multifunctional ” and externalities such as rural development and landscape would be underproduced, while some forms of pollution (such as nitrogen runoff) would be overproduced without government intervention. Meanwhile, the United States has raised the concern that multifunctionality is primarily an argument to transfer income to producers. One way to try and determine how much of these non-commodity payments are directed to externalities and how much is intended to distribute income to producers is to analyze the variation of the programs among the different member states of the EU. We estimate the degree to which environmental characteristics, agricultural characteristics and political economy variables determine the objective and amount of funding each member states uses to
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".