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Record W4413226624 · doi:10.1017/s1474745625100992

Recalibration, Shielding and Containment: How the World Trading System De-risks from China and the United States

2025· article· en· W4413226624 on OpenAlexaff
Wolfgang Alschner

Bibliographic record

VenueWorld Trade Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Trade Organization Law
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsChinaMultilateralismInternational tradeTrade warEconomicsRest (music)Corporate governanceCoercion (linguistics)Global governanceBusinessInternational economicsPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

Abstract The two economic superpowers operate increasingly outside WTO norms. China's reliance on non-market practices challenges the competitive equality among WTO members, while the US, under a second Trump administration, has unilaterally raised tariffs in defiance of multilateral rules. This essay examines how the rest of the world is de-risking from the two rogue superpowers while shoring up trade multilateralism. It identifies three interlinked strategies: (1) recalibration – reducing trade dependency through targeted trade remedies against China and narrow bilateral agreements with the US; (2) shielding – collective and unilateral responses to economic coercion of both superpowers; and (3) containment – preventing illegality from spreading to the rest of the world. Together, these modes of governance not only mitigate systemic spillovers from rule-breaking but also help rebalance global trade by addressing structural imbalances in Chinese overproduction and US overconsumption. In doing so, the rest of the world may lay the groundwork for a renewed and more resilient multilateral trading system.

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)0.002
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: none
Teacher disagreement score0.978
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
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 head0.025
GPT teacher head0.294
Teacher spread0.269 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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