The Puzzle of Agricultural Exceptionalism in International Trade Policy
Bibliographic record
Abstract
This article first seeks to demonstrate the exceptional levels of protectionism accorded to the agricultural sector, especially in many developed countries. It reviews the principal protectionist measures employed: domestic subsidies and price supports, production restrictions, and border measures; describes briefly the disciplines applicable to these measures under World Trade Organization law; and then surveys empirical evidence on the extent of protectionism that prevails in the agricultural sector in many countries. Next, it evaluates the principal normative justifications often offered for exceptional levels of agricultural protectionism: ensuring access to affordable food; ensuring a livable income for farmers; and preserving traditional rural lifestyles and communities. It finds that these are not especially compelling either relative to many other economic sectors or in terms of first-best policy responses to the normative concerns in question. The article then considers political economy explanations for exceptional levels of protectionism in agriculture—including Public Choice explanations and the transitional gains trap—which, while providing some purchase on the phenomenon, are again not completely compelling. The article concludes with some observations on how liberalization of trade in agricultural products might be advanced in the future.
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.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".