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Record W3205008190 · doi:10.22004/ag.econ.151447

Socio-economic Considerations and International Trade Agreements

2013· article· en· W3205008190 on OpenAlexaff
Stuart J. Smyth, José Benjamin Falck‐Zepeda

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInternational tradeConvention on Biological DiversityConventionBusinessInclusion (mineral)LegislationBiosafetyCorporate governanceEconomic integrationInternational economicsEconomicsPolitical scienceFinance

Abstract

fetched live from OpenAlex

The provision for the inclusion of socio-economic considerations in domestic regulatory frameworks pertaining to living modified organisms has been established by Article 26 of the Cartagena Protocol on Biosafety to the Convention on Biological Diversity. Many countries are considering, or have considered, inclusion of socio-economic aspects in their domestic legislation, raising international concern that socio-economic risk assessments will become a mandatory part of approval processes and further complicate the approval, and international trade, of new genetically modified crops. Barriers to international trade, unfortunately, enjoy a long and robust history. The objective of this article is to review the various international agreements that have a governance capacity pertaining to international trade and assess how these agreements might interpret the domestic implementation of socio-economic risk assessments. The result of this will be a clearer understanding of what cost and benefit tradeoffs will be required by countries that have included, or are planning to include, socio-economic considerations as part of their domestic regulatory framework.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.983

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.000

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 head0.047
GPT teacher head0.235
Teacher spread0.189 · 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

Citations7
Published2013
Admission routes1
Has abstractyes

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