MétaCan
Menu
Back to cohort
Record W2283764106

SPS Measures and the Export of Primary Products Protection and Protectionism

2005· article· en· W2283764106 on OpenAlexaboutno aff
Gordon Anderson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural safety and regulations
Canadian institutionsnot available
Fundersnot available
KeywordsProtectionismInternational tradeBusinessNorm (philosophy)Balance (ability)Product (mathematics)Precautionary principleTechnical barriers to tradePolitical scienceInternational economicsEconomicsTrade barrierLawMedicine
DOInot available

Abstract

fetched live from OpenAlex

Since the completion of the Uruguay Round Canada has been involved in two major disputes concerning the Agreement on the Application of Sanitary and Phytosanitary Measures. The Appellate Body reports in these two disputes have been critical in determining the obligations of countries under the SPS Agreement. Although Canada was successful in those cases the Appellate Body reports suggest that future disputes may prove more difficult to win. This paper will focus primarily on the nature of the risk assessment that is required to be undertaken under the SPS Agreement and in doing so will consider SPS measures from two perspectives. First that of an exporter facing SPS barriers to the particular product being exported and secondly that of a country wishing to prevent the introduction of damaging organisms and therefore seeking to impose quarantine restrictions to achieve appropriate protection. The paper will also raise the question of whether the SPS Agreement and associated case law suggest that a proper balance has been developed between genuine SPS and trade needs and consider whether the lack of success in defending SPS measures is likely to the norm in future. These issues are of major concern to all countries but particularly those that are heavily dependent on the export of primary products.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.209

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)0.0000.000

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 head0.021
GPT teacher head0.169
Teacher spread0.148 · 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.

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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same topicAgricultural safety and regulationsFrench-language works237,207