Comparative Analysis of Support to Agriculture in the QUAD Countries in 1986-2014
Bibliographic record
Abstract
The purpose of this paper is a comparative analysis of support provided to agriculture sector by the QUAD countries in 1986-2014. The authors examined the changes in levels and structures of this support and tried to assess it from the point of view of its impact on the QUAD economies and markets. In the analysis conducted there were used especially the OECD data and indexes measuring state support to agriculture including: Total Support Estimate, Producer Support Estimate, General Services Support Estimate and Consumer Support Estimate. In the last three decades in all the examined economies, there has been a reduction in agricultural support in relation to GDP, although no distinct change has occurred in terms of the amount of aid in absolute terms (in the US its value even increased almost twice). As regards the changes in structure of support, the most favorable tendencies took place in the European Union where the market price support (MPS), i.e. the most distorting aid to the functioning of the market mechanism, was significantly reduced. One can also positively assess the support structure in the United States where about half of the agricultural budget is earmarked to consumers. Canada has very good economic outcomes as regard the agriculture sector even though it allocates the least amount of financial resources to support agriculture in relation to GDP among all the QUAD economies. However, despite a large part of this support is in the form of general services (GSSE), the country is characterized by an unfavorable trend of increasing expenditure on price support. Throughout the period considered the most harmful support policy from the point of view of market competition was led by Japan though it has affected to a lesser extent the functioning of international agri-food markets due to the lower importance of Japanese agricultural production and exports in the world economy in comparison to the EU and the US.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".