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Record W2167778600

Issues on Adoption, Import Regulations, and Policies for Biotech Commodities in China with a Focus on Soybeans

2003· article· en· W2167778600 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMOspace Institutional Repository (University of Missouri) · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
Fundersnot available
KeywordsChinaAgricultureAgricultural biotechnologyEuropean unionCommodityBiotechnologyBusinessRapeseedAgricultural scienceAgricultural economicsInternational tradePolitical scienceEconomicsBiologyAgronomyLaw
DOInot available

Abstract

fetched live from OpenAlex

Since the introduction of biotech commodities in 1996, farmers in the United States have rapidly adopted this new technology for production, primarily for soybeans, cotton, and corn (Nelson, 2001). The United States is the largest grower of biotech crops in the world, with 101.5 million acres under cultivation in 2003 (United States Department of Agriculture [USDA] National Agricultural Statistics Service [NASS], 2003). In the United States, adoption of biotech soybeans reached 81% in 2003, 73% for biotech cotton, and 40% for biotech corn. Globally, in 2002 about 45% of soybean acreage was planted with biotech soybeans, 11% with biotech corn, 20% with biotech cotton, and 11% with biotech rapeseed (USDA Foreign Agricultural Service [FAS], 2003a). China has become the fourth largest grower of transgenic commodities, following the United States, Argentina, and Canada. China’s dominant biotech commodity is Bt cotton, with 5.2 million acres planted in 2002 (USDA FAS, 2003a). As of this writing, China has not approved the adoption of other major transgenic agricultural commodities, such as soybeans, corn, rice, or wheat. Given food safety concerns, there is global controversy about biotech foods. Many countries (particularly developed countries that import food) have implemented regulations to restrict adoption and import of biotech food products. In the late 1990s, six European Union (EU) member nations (Austria, France, Germany, Greece, Italy, and Luxembourg) banned imports of transgenic corn and rapeseed that were approved by the European Union (USDA FAS, 2003b). In late 1998, the EU imposed a five-year de facto moratorium on approving new transgenic varieties, which effectively prohibits most US corn exports to Europe. In May 2003, the United States, Argentina, and Canada filed a World Trade Organization (WTO) dispute against the EU over its moratorium (USDA, 2003; USDA FAS, 2003b). “The first step in a WTO dispute is to request and conduct consultations during the next 60 days. WTO procedures were designed to encourage parties to resolve their differences” (USDA FAS, 2003b). However, after consultations, in August 2003 the US took the next step by requesting a dispute settlement panel to hear arguments in its WTO challenge to the EU’s biotech moratorium. “Dispute settlement procedures, including appeal, typically take a total of 18 months” (USDA FAS, 2003b, 2003f). Japan also has strict regulations for biotech food imports. In 2000, Japanese legislation was introduced to prevent imports of food products that contain transgenic varieties not yet approved in Japan (USDA FAS, 2003d). Japan’s biotech testing focuses on transgenic products approved for commercialization abroad but not yet approved in Japan (e.g., StarLink corn is not approved for any use in Japan). In Japan, foods found Mary A. Marchant University of Kentucky

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.208
Teacher spread0.193 · 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