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Record W4412196942 · doi:10.1111/twec.13730

Global Governance, Economic Sanctions and Agricultural Trade in a Fragmenting World Economy

2025· article· en· W4412196942 on OpenAlexaff
Sylvanus Kwaku Afesorgbor, Fabio Gaetano Santeramo, Sandro Steinbach

Bibliographic record

VenueWorld Economy · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Sanctions and International Relations
Canadian institutionsUniversity of Guelph
FundersNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsSanctionsAgricultureCorporate governanceWorld tradeWorld economyInternational tradeEconomic sanctionsEconomicsProtectionismBusinessEconomyPolitical scienceGeographyFinance

Abstract

fetched live from OpenAlex

ABSTRACT Global governance and agricultural trade are undergoing a substantial transformation driven by geopolitical shifts, declining multilateralism and the rise of economic sanctions. This editorial synthesises contributions from a collection of invited works that examine the impacts of these changes on trade systems, food security and value chains. The collection explores how the shift from multilateralism to regionalism, the spread of sanctions and evolving governance frameworks influence agricultural trade and policy outcomes. Key themes include the resilience of agri‐food systems to disruptions, the role of trade agreements in mitigating shocks and the balance between environmental goals and trade facilitation. These studies call for a more adaptive governance framework that can safeguard agricultural trade and food systems amid rising geopolitical tensions and institutional fragmentation.

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)0.001
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0050.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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