Bibliographic record
Abstract
This article examines the invention and exhibitions of the panda circus to explore the political, economic, and cultural influence of the giant panda on China–Japan diplomacy and the transnational cultural economy. Using oral history interviews and archival materials, the authors explain how, in 1981, a giant panda named Wei Wei became China’s first panda entertainer in Japan, embarking on a cross-country tour supported by friendship-city agreements and grassroots friendship movements. By discussing Wei Wei’s unexpected and sometimes ferocious responses to human demands, as well as Japanese media reporting on his “rebellion”, the authors show how Wei Wei’s behaviour raised Japanese public awareness of the giant panda’s individuality and agency. The circus tour not only facilitated municipal-level China–Japan relations but also generated a new mode of anthropomorphizing the giant panda—one that challenged consumerist representations and helped Japanese audiences recognize the giant panda’s suffering. The authors argue that Wei Wei’s “rebellion” disrupted human political expectations and economic transactions in this episode of China–Japan diplomacy, contributing to a re-envisioning of bilateral relations beyond a strictly political-economic framework. Overall, the article offers an interdisciplinary, trans-Asia approach that explores the intersections of animal agency, emotional labour, international relations, media, and performance.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.151 | 0.036 |
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".