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Record W3121447155

Effects Of The Canadian Wheat Board On The U.S. Wheat Industry

2004· article· en· W3121447155 on OpenAlexaboutno aff
Won W. Koo, Hyun Joung Jin, Jeremy Mattson, Richard D. Taylor, Guedae Cho

Bibliographic record

VenueAgribusiness & Applied Economics Report · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationInternational tradeSubsidyBusinessAgricultural economicsInternational economicsEconomicsMarket economyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

The practices of the Canadian Wheat Board (CWB) are an important issue in U.S. - Canada trade disputes and WTO negotiations. This study analyzes the CWB?s effect on U.S. producers by reviewing findings from previous research and developing models to analyze CWB wheat exports to the United States and the competitive structure of Canadian wheat exports in the world market. U.S. grain producers could benefit from the removal of the CWB as the United States could become more competitive in export markets. However, elimination of the CWB could also result in an increase in Canadian wheat exports to the United States as Canadian producers near the border could sell directly to the United States to take advantage of market opportunities. The net effect is difficult to quantify. The net benefits may be significant in the short run, but reduced significantly in the long run. Similarly, if Canada reforms its wheat board by eliminating trade-distorting subsidies, the United States may increase its exports and Canadian exports to the United States may increase. The net benefits from reforming the CWB could be greater than those from eliminating it. However, the United States could benefit the most from complete elimination of state trading enterprises (STEs), since they have elements distorting trade flows and the United States competes with several STEs in the world wheat market.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.181
Teacher spread0.156 · 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 designTheoretical or conceptual
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

Citations0
Published2004
Admission routes1
Has abstractyes

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