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Record W4406627426 · doi:10.54648/eerr2025005

Climate Change and Biodiversity as an Essential Element of EU External Trade Relations FTAs: Legal Effects and Policy Implications in EUCentral America Trade and Sustainable Development Relations

2025· article· en· W4406627426 on OpenAlexaboutno aff
Markus W. Gehring, Jorge Cabrera

Bibliographic record

VenueEuropean Foreign Affairs Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsnot available
Fundersnot available
KeywordsElement (criminal law)Climate changeSustainable developmentPolitical scienceBiodiversityInternational tradeEconomicsEcologyBiologyLaw

Abstract

fetched live from OpenAlex

Obligations on climate change and biodiversity are increasingly evident not just in the European Union’s (EU’s) environmental policy and cooperation, including through the rapid ratification of and attempts to strengthen implementation and compliance with the Paris Agreement and the Convention on Biological Diversity (CBD), but also in other economic relationships of the EU. While sustainable development has been an objective of the EU’s international trade agreements since 1994, efforts to address climate change and biodiversity originally appeared almost as an afterthought in these agreements. This article documents a fundamental shift in the EU’s external relations through the meaningful inclusion of cooperation on climate change and biodiversity in the EU’s trade and investment agreements, and provides an analysis of the legal and policy consequences. It argues that including global response to climate action (and potentially biodiversity) as an essential element in a bilateral or inter-regional economic relationship changes the nature of that relationship. The Paris Agreement and the new Kunming- Montreal Global Biodiversity Framework (GBF) contain long and medium-term objectives that all trading partners will want to achieve. While the legal text is designed not to be used in practice, the elevation of both climate change now and biodiversity in the future to an essential element, fulfils an important signalling function that permeates the entire trade relationship and has the potential to change its basis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.008
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2025
Admission routes1
Has abstractyes

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