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Record W2433496355 · doi:10.1017/s2047102516000054

Globalization and the Animal Turn: How International Trade Law Contributes to Global Norms of Animal Protection

2016· article· en· W2433496355 on OpenAlexaff
Katie Sykes

Bibliographic record

VenueTransnational Environmental Law · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsAnimal welfareEnforcementInternational lawJurisprudenceInternational tradeEnvironmental lawPolitical scienceGlobalizationBusinessTribunalNegotiationLaw and economicsLawEconomicsBiology

Abstract

fetched live from OpenAlex

Abstract Many animal and environmental activists think of international trade law as a block to the achievement of their goals and perceive the World Trade Organization (WTO) as a threat to animals. Yet, the first legal decision of an international tribunal to devote careful, sustained attention to animal welfare issues comes from the WTO, in the EC – Seal Products decision. This article argues that international trade law is currently an important, although under-acknowledged, locus for the development of global norms concerning the protection of animals, and that animal conservation and animal welfare can be seen as aspects of a single overarching principle of animal protection. International trade law contributes to animal protection in two ways. Firstly, WTO jurisprudence has recognized animal protection as a legitimate basis for invoking exceptions to trade rules (as in EC – Seal Products ). Secondly, international trade negotiations enhance cooperation on the implementation and enforcement of existing conservation obligations (as in the new Trans-Pacific Partnership’s Environment Chapter).

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 score0.910
Threshold uncertainty score0.561

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 studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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

Citations38
Published2016
Admission routes1
Has abstractyes

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