Multilateralism and Soft Power Made-in-China: (re)Adjusting Role Conception to Meet International Expectations
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".