The Digital Silk Road in Europe: China’s Soft Power Maneuvers at Euro 2024
Bibliographic record
Abstract
In recent years, China has focused on expanding the Belt and Road Initiative (BRI) and the Digital Silk Road (DSR) in Europe. Despite the presence of giants such as Huawei, the DSR has faced various challenges due to the security concerns of European states, further influenced by the positions of the European Union (EU) and the United States of America (USA). One of Beijing's responses involves the 2024 European Football Championship, whose main sponsors are Chinese. Considering that this action falls under the category of soft power and Public Diplomacy, this article analyses how these sponsorships can contribute to the expansion of the DSR in Europe. Thus, our investigation unfolds around the following research question: How did China use diplomacy and soft power to promote the Digital Silk Road during Euro 2024? Using a primarily qualitative approach, our study concluded that China, through its companies, seeks to entice European consumers, making them more receptive to the potential expansion of its digital corridor in European territory.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".