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Record W1509210383

U.S. Agricultural Trade: Trends, Composition, Direction, and Policy

2011· book· en· W1509210383 on OpenAlexaboutno aff
Charles E. Hanrahan, Beverly A. Banks, Carol Canada

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2011
Typebook
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureInternational tradeSubsidyEuropean unionCommodityAgricultural economicsInternational economicsEconomicsIndex (typography)Agricultural policyBalance of tradeBusinessCommon Agricultural PolicyProduct (mathematics)GeographyMarket economy
DOInot available

Abstract

fetched live from OpenAlex

Agricultural imports are expected to reach $64.5 billion.The agricultural trade surplus, projected to be $3.5 billion, is at its lowest level in 19 years.Exports of bulk commodities (e.g., soybeans, wheat, and feed grains) remain significant, but exports of high-value products (HVPs), such as meats, fruits, and vegetables, are increasing.HVPs accounted for 62% of total U.S. agricultural exports in FY2005.Leading markets for U.S. agricultural exports are Canada, Mexico, Japan, China, the European Union, Taiwan, and Korea.The United States dominates world markets for corn, wheat, and cotton.Brazil has overtaken the United States as the world's leading supplier of soybeans.Brazil is the world's leading supplier of beef to world markets, while the U.S. share has declined since the U.S. discovery of a cow infected with "mad cow disease" in 2003.The United States, European Union, Australia, and New Zealand are dominant suppliers of dairy products in global agricultural trade.Most U.S. agricultural imports are high-value products.For some imports (grains, meats, horticultural products), similar products are produced in the United States; production of other categories of imports (bananas, coffee, cocoa) is very limited.The biggest import suppliers are the European Union, Canada, and Mexico, which together provide 58% of total U.S. agricultural imports.Australia, Brazil, New Zealand, Indonesia, and Colombia are also major suppliers of agricultural imports to the United States.Among the fastest-growing markets for U.S. agricultural exports are Canada and Mexico, both partners with the United States in the North American Free Trade Agreement (NAFTA).U.S. agricultural exports to China, recently a member of the World Trade Organization, have grown at an annual rate of 16% since 1992.Both the EU and the United States subsidize their agricultural sectors, but overall the EU out-subsidizes the United States.Recent reforms of the EU's Common Agricultural policy shift substantial spending into direct income support decoupled from production and into rural development.Canada supports some sectors (e.g., dairy and poultry) more than others.Australia provides less support to its agriculture.Single desk sellers with monopoly powers operate wheat markets and markets for some other commodities in Canada and Australia.Export subsidies are more important in the EU than in the United States; border measures (tariffs) are more important in Canada than in either the United States or the EU.Australia operates a mix of trade measures.The United States is the dominant supplier of foreign food aid, followed by the EU, Canada, and Australia.U.S. and other major food aid donors provide commodities mainly for development assistance or emergency relief.This report will be updated.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.152
Teacher spread0.141 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2011
Admission routes1
Has abstractyes

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