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Record W4392471066 · doi:10.1007/s12140-024-09424-0

Multilateralism and Soft Power Made-in-China: (re)Adjusting Role Conception to Meet International Expectations

2024· article· en· W4392471066 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEast Asia · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsCanadian Federation of University Women
FundersFundação para a Ciência e a TecnologiaUniversidade do MinhoAalborg Universitet
KeywordsMultilateralismSoft powerChinaPower (physics)Political scienceHard powerInternational tradePolitical economySociologyEconomicsLawPolitics

Abstract

fetched live from OpenAlex

Abstract This article addresses the specificities of the new multilateralism made-in-China under Xi Jinping. We argue that China has been investing in a combination of Soft Power and Multilateralism to foster a friendly worldwide environment whilst promoting China’s geopolitical reemergence. Drawing on role theory, we assess whether there has been a shifting trend on China’s soft power and multilateralism, to cope both with international expectations on China’s new role and China’s own role conception. We conclude that China’s gradual turn towards multilateralism and soft power is a complementary strategy to China’s longstanding use of bilateralism. It provides China with new institutions and ways to prosper as Chinese interests are no longer effectively fulfilled within the old Bretton Woods system. This article aims to deepen the existing literature on China’s soft power, whilst highlighting the novel developments in China’s multilateral initiatives and soft power including the impact of EU’s de-risking approach toward China – not yet addressed by current studies.

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.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.633

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.305
Teacher spread0.292 · 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