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Record W2889115517 · doi:10.1111/cjag.12185

Impact of the Chinese embargo against MIR162 corn on Canadian corn producers

2018· article· en· W2889115517 on OpenAlexvenueaboutno aff
Troy G. Schmitz

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
FundersArizona State University
KeywordsBushelRevenueChinaAgricultural economicsAgricultural scienceAgronomyBiologyEconomicsGeographyAcre

Abstract

fetched live from OpenAlex

Abstract In 2009, Syngenta created two new insect‐resistant corn varieties known as Agrisure Viptera and Agrisure Duracade, which contain the MIR162 biotechnology‐enhanced genetic trait. These varieties were approved for commercial release in North America in 2010 and were planted in spring 2011. China imposed an embargo on corn imports from North America beginning on November 20, 2013, because of its zero‐tolerance policy with respect to unapproved genetic traits in imported crops. The embargo was not lifted until December 14, 2014. The embargo led to increased availability of North American corn and a reduction in the price of corn realized by Canadian producers. The relative price of a substitute method was applied to weekly data on Ontario corn prices and Saskatchewan feed barley prices. The Chinese embargo against MIR162 corn caused the corn price received by Canadian farmers to drop by an estimated 1.24% or 5.32 cents/bushel. But for the Chinese embargo against MIR162 corn, Canadian corn producers would have realized an estimated additional $29.7 million in revenue in 2013/2014.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.179
Teacher spread0.147 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2018
Admission routes2
Has abstractyes

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