Visitors’ experiences at a controversial exhibition on rhino conservation and de-extinction
Bibliographic record
Abstract
This study examines visitors' experiences at ‘The Lost Rhino' (TLR), a controversial exhibition hosted by the Natural History Museum (London), focusing on rhino conservation and the concept of de-extinction. The exhibition, which integrates art, science, and environmental issues, presents provocative topics - challenging visitors’ beliefs, values, and ethical considerations. Using mixed methods, we gathered data through surveys, interviews, and video recordings to explore how visitors experienced TLR and which features of controversial exhibitions they engaged with during their visit. Findings reveal that while most visitors did not initially perceive TLR as controversial, they experienced significant emotional responses, particularly sadness, and engaged in critical reflections on human impacts on biodiversity and the ethical implications of technological interventions in nature. This study contributes to understanding the role of museums in fostering public discourse on pressing controversial environmental issues and the potential for art-science exhibitions to provoke meaningful dialogue and reflection on conservation practices and the ethical dilemmas associated with de-extinction. We suggest that museum education should foster critical reflection, emotional engagement, and public dialogue on pressing local and global issues by integrating art, science, and ethics into thought-provoking exhibitions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".