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Green Diplomacy at the Crossroads of International Law and International Relations

2025· article· W7117459909 on OpenAlexaboutno aff
Miranda Gurgenidze, Emilia Alaverdov

Bibliographic record

VenueScientific Journal „Spectri“ · 2025
Typearticle
Language
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsDiplomacyInternational relationsTreatyInternational lawNexus (standard)Environmental governanceGlobal governanceClimate governanceOperationalizationInternational security

Abstract

fetched live from OpenAlex

This article examines the evolution of green diplomacy as a central instrument at the nexus of international law and international relations, highlighting its transformative role in contemporary global governance. While environmental diplomacy historically revolved around treaty negotiation and compliance, recent developments indicate a shift toward using environmental objectives as mechanisms of geopolitical influence, strategic cooperation, and economic leverage. Drawing on foundational legal instruments, including the UNFCCC, Kyoto Protocol, Paris Agreement, Montreal Protocol, CBD, CITES, UNCLOS, the Stockholm Declaration, and the 2030 Agenda, this study demonstrates how international law establishes the normative and institutional foundations of climate action, while diplomatic processes operationalize these commitments within political practice. Through integrated case studies, the article analyzes the dynamics of EU–China climate collaboration and competition, the United States’ withdrawal and return to the Paris Agreement, climate justice diplomacy led by Small Island Developing States, and the Carbon Border Adjustment Mechanism as a tool of green trade. The research reveals that green diplomacy now extends far beyond environmental protection, shaping global power structures, trade regimes, financial flows, and security agendas. Ultimately, the findings suggest that green diplomacy is emerging as a multidimensional governance framework capable of reconfiguring international relations in an era defined by climate urgency, technological transition, and heightened environmental interdependence.

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)0.009
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.050
Scholarly communication0.0140.013
Open science0.0010.007
Research integrity0.0030.007
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 head0.016
GPT teacher head0.311
Teacher spread0.295 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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Same venueScientific Journal „Spectri“Same topicTransboundary Water Resource ManagementFrench-language works237,207