The welfare of wild animals in zoological institutions: are we meeting our duty of care?
Bibliographic record
Abstract
Across the world there are many different species of wild animals maintained in zoological institutions of one sort or another for a variety of purposes. Their welfare is directly dependent upon the quality of life they experience, which in turn is driven by the understanding the owner/keeper has of the needs of the animals. This ‘understanding’ may or may not be informed by scientific knowledge. Sub‐optimal conditions and/or husbandry practices can result in injury, disease and poor mental health; hence, it is critical that environmental conditions, management and husbandry techniques are employed that promote positive physical and psychological health for all wild animals in human care. An individual needs good psychological health, as well as good physical health, to achieve good welfare. Further complicating the issue is the variation in existing animal‐welfare legislation and in the range of species afforded protection under the legislation between different countries. This paper emerges from an initiative to improve and promote good welfare in zoological institutions that have suboptimal conditions in countries where help is needed most. This initiative included fostering relationships with zoo and aquarium officials and regulatory bodies based on an assessment of what needs to be done for specific facilities to improve welfare for the animals under their care. An approach to advancing animal welfare was developed by establishing the fundamental requirements for the welfare of wild animals in human care and developing an accompanying assessment tool. This approach incorporated the Five Domains animal‐welfare model as the central evaluative device.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".