Civilised Panda viewing and visitor restrictions: an ethics of care approach to managing tourist misbehaviour
Bibliographic record
Abstract
Introducing measures to regulate tourist misbehaviour at visitor attractions is an ongoing challenge. While previous research has explored the factors behind visitor misconduct, little attention has been given to how these measures are received and interpreted by the public. This study addresses this gap by investigating how restrictions to misbehaving visitors influence public reactions through the lens of the ethics of care. This framework is particularly relevant in China, where ‘civilised tourism’ has become a national discourse promoting responsible tourist behaviour. Using theme and sentiment analysis, the study examines 319 comments from 27 public announcements on WeChat posted by the Chengdu Research Base of Giant Panda Breeding following reports of tourist misbehaviour. The findings suggest that such restrictions elicit collective moral reinforcement towards misbehaviours, with WeChat users actively endorsing the measures to uphold civilised tourism norms. By integrating the ethics of care into discussions on tourist misbehaviour, this research underscores the importance of fostering responsible human-animal interactions and civil behaviours. Given China's increasing emphasis on wildlife conservation and the growing role of social media in shaping public discourse, this study aligns with China's national strategy of civilised tourism, offering insight into how science-based governance enhances public engagement in wildlife protection.
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How this classification was reachedexpand
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".