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Record W2057672103 · doi:10.1162/glep.2010.10.2.80

Norms, Institutions and Social Learning: An Explanation for Weak Policy Integration in the WTO's Committee on Trade and Environment

2010· article· en· W2057672103 on OpenAlexaff
Melissa Gabler

Bibliographic record

VenueGlobal Environmental Politics · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNormativeNorm (philosophy)Corporate governanceSustainable developmentSustainabilityGlobal governancePolitical sciencePolicy learningEconomicsEconomic systemLawManagementEcology

Abstract

fetched live from OpenAlex

The United Nations Conference on Environment and Development (UNCED) recognized that sustainable development can only be actualized if environmental norms are integrated into other areas of policy across levels of governance. This article examines the Committee on Trade and Environment of the World Trade Organization (WTO) to answer the question of why actors' efforts to enhance the mutual supportiveness of trade and environmental norms have resulted in minimalist policy outcomes. I first introduce a framework for analyzing norms and their levels of compatibility and a social learning explanation for policy integration emphasizing the importance of normative and institutional conditions. Second, I show that low levels of both norm compatibility between UNCED and WTO and institutional capacity in the WTO for learning have contributed to weak integration. The approach contributes to constructivist theory development and the findings provide insights to policy-makers grappling with how to support the integration of norms and institutions in global governance.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.964
Threshold uncertainty score0.625

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 studies0.0010.001
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 head0.020
GPT teacher head0.290
Teacher spread0.270 · 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 designTheoretical or conceptual
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

Citations28
Published2010
Admission routes1
Has abstractyes

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