Are They Really Chinese? Examining Chinese Audiences’ Emotions and Perceptions Toward Naturalized Athletes at the 2022 Winter Olympics
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.
Bibliographic record
Abstract
As sport has become more globalized, there has been an increase in the number of athletes who have changed their nationality to maximize their chances to compete in international competitions. In order to maximize its chances at its home hosted Winter Olympic Games, the Chinese government authorized many foreign-born athletes to gain Chinese citizenship to compete for China. The purpose of the study was to explore how Chinese social media users perceived athlete naturalization of Chinese athletes during the 2022 Beijing Olympic Games. Through sentiment analysis and thematic analysis, results found that Chinese spectators generally had positive emotions toward these naturalized Olympians. Online discussions mainly focused on three topics: expressing their attitudes toward athlete naturalization, questioning the legitimacy of the strategy, and discussing athletes’ heritage and cultural identities. This research hopes to broaden our understanding of the sport migrant issue in China, the perceptions of athletes who have naturalized, and the sentiments that Chinese consumers have of naturalized athletes at the Winter Olympic Games that were held in their country.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it