Wildlife conservation and animal welfare: two sides of the same coin?
Bibliographic record
Abstract
Abstract Human activities deprive wild animals of their life requisites by destroying or impoverishing their surroundings, causing suffering of individuals. Yet, the notion that animal welfare applies to wildlife has escaped many animal welfarists and conservationists. A well-accepted and applied ethical foundation for animal conservation that considers animal welfare is lacking. We address this by examining how worldviews of conservationists and animal welfarists are related. The clear conceptual link is that individuals within anthropogenically disturbed populations often endure suffering caused by humans. Accordingly, our objectives are to provide an overview of wildlife conservation, integrate ethical aspects of wildlife conservation and animal welfare, and encourage a ‘wildlife welfare’ ethic among conservationists. We describe the relationship between contemporary socioeconomic and environmental conditions and the impoverished status of North American wildlife. We then describe the ecological plight of large mammalian carnivores in North America. Finally, as a case study, we focus on the tenuous lives of grey wolves(Canis lupus)living in the midst of human-dominated landscapes. We conclude that the suffering wildlife endures because of humans is a collective responsibility that presents a moral imperative for animal welfarists and conservationists alike. Habitat destruction and impoverishment deprives species of life requisites, causing trauma, prolonged suffering, and eventually death. We suggest that a shared doctrine of animal welfare principles is needed, such as a modified version of the internationally recognised Five Freedoms. In essence, this would be an ethical affirmation for conservationists and animal welfarists.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.058 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".