Human Relations with Mesopredators
Bibliographic record
Abstract
In contrast to large carnivores, smaller carnivores, sometimes called mesopredators or mesocarnivores, are considered less dangerous to humans and livestock and are less charismatic, popular, and targeted in conservation research. However, small carnivores are important participators in ecosystems and have important relationships with people, human habitats, livestock, and domestic animals. In some cases, mesopredators can become apex predators through the regional or local extinction of larger species, but there is some disagreement on the size range of mammalian mesopredators. Avian mesopredators may be medium-sized birds of prey, but in terms of prey taken, the largest birds of prey, the eagles, are similar to the mesopredators of mammals such as medium-sized dogs and cats. Human attitudes toward mesopredators tend to be less intense because these smaller animals are generally less dangerous to humans and associated animals, have smaller ranges, and appear to be more amenable to semi-domestication as pets. This chapter examines case studies of human attitudes toward small carnivores, including mammals, birds, and reptiles in the context of human habitats and land use. The evidence suggests that smaller predators have been neglected in the conservation literature and the human dimension of wildlife literature in favor of larger, more charismatic and dangerous carnivores. However, this oversight is important for the study of both wildlife ecology and the human dimension of wildlife. The chapter takes a social science perspective, particularly that of conservation psychology, and presents evidence that this approach is important for the conservation biogeography of wildlife. It is concluded that conservation psychology is important for the study of conservation biogeography and human-wildlife relationships, even when focused on smaller predators. This contributes to nature conservation policy and protected area management.
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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 | 0.001 | 0.003 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".