Ubiquitous Love or Not? Animal Welfare and Animal-Informed Consent in Giant Panda Tourism
Bibliographic record
Abstract
Scholars argue that the ubiquity of the "virtual panda"-the panda people meet in zoos and consume as souvenirs, online memes, or videos-exists in a state of hybridity between wild and domesticated. The species has garnered a significant amount of attention because of their iconic status and because of how cute they are to an adoring crowd. However, given the degree of regard tourists have for the panda, there is a dearth of research on different types of visitors to captive panda venues. In filling this gap, we investigated (1) how deeply Chinese "fans" and "non-fans" consider the welfare of captive giant pandas, and (2) if these groups differ in their assessment of whether giant pandas consent to being used as tourist attractions. In both aims, we apply a recent model on animal welfare and animal consent to giant pandas of the Chengdu Research Base of Giant Panda Breeding.
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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 | 0.013 | 0.026 |
| 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 | 0.015 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".