Dangerous animals in captivity: Ex situ tiger conflict and implications for private ownership of exotic animals
Bibliographic record
Abstract
Abstract The risks associated with tiger attacks on people in the wild are well documented. There may currently be more tigers in captivity than in the wild, but relatively little is known about the risks of injury or death associated with owning and managing captive tigers and other large carnivores. The purpose of this study was to conduct a global assessment of attacks by captive tigers on people, with particular emphasis on cases in the United States. Our analysis of 30 international media sources and additional documents uncovered 59 unique incidents in 1998–2001 in which people were reportedly injured or killed by captive tigers. In the United States, seven people were reportedly killed and at least 27 were injured—a rate of 1.75 fatal attacks and at least nine nonfatal attacks per year. All but one fatal attack in the United States occurred in situations where tigers were privately owned or held in private facilities. Forty‐two percent of the victims were classified as visitors, and almost one‐quarter of the victims were under the age of 20. These results suggest that the victims underestimated the dangers posed by direct contact with these animals. In this work we review current legislation regarding captive ownership of tigers and other large exotic animals, and contradict claims by those who support private ownership of tigers and other large felids that the risks associated with owning and viewing these animals are insignificant. We conclude that the growing number of people who own tigers and other large exotic animals is cause for concern because of the danger to the animals, the handlers, and the public. The problem of private ownership of dangerous exotic animals has broad implications for tiger and large‐carnivore conservation, public health, and animal welfare. We support the regulation of private ownership of dangerous exotic animals, and encourage scientific analysis of this contentious issue. Zoo Biol 22:573–586, 2003. © 2003 Wiley‐Liss, Inc.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".