Reforming Agricultural Support for Improved Environmental Outcomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Agricultural support has changed substantially in both rich and poor countries in recent years. In rich countries, there has been a strong move to decoupled subsidies and a fall in average rates of protection. In developing countries, market price support remains the dominant form of protection, and average rates of support have risen—breaking the traditional pattern of taxing agriculture. Emissions from agriculture and land use change have contributed up to a third of total greenhouse gas emissions, with beef, milk and rice production accounting for more than 80% of agricultural emissions. Agricultural support was biased against emission‐intensive goods until recent years and is now only slightly biased toward them. Although emission intensities are relatively higher in the developing countries, they have fallen far more rapidly in developing countries than in the rich countries in the past quarter century, as agricultural productivity has grown in developing countries. Policy reform will be challenging given the strong political‐economy support for the current structure of protection. Increasing investments in research and development to raise productivity and lower the emissions intensity of agricultural output would help agriculture and the environment. JEL CLASSIFICATION F18; F64; Q18; H23; Q58
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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