Fear of the human “super predator” far exceeds the fear of large carnivores in a model mesocarnivore
Why this work is in the frame
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Bibliographic record
Abstract
The fear (perceived predation risk) large carnivores inspire in mesocarnivores can affect ecosystem structure and function, and loss of the “landscape of fear” large carnivores create adds to concerns regarding the worldwide loss of large carnivores. Fear of humans has been proposed to act as a substitute, but new research identifies humans as a “super predator” globally far more lethal to mesocarnivores, and thus presumably far more frightening. Although much of the world now consists of human-dominated landscapes, there remains relatively little research regarding how behavioral responses to humans affect trophic networks, to the extent that no study has yet experimentally tested the relative fearfulness mesocarnivores demonstrate in reaction to humans versus nonhuman predators. Badgers (Meles meles) in Britain are a model mesocarnivore insofar as they no longer need fear native large carnivores (bears, Ursus arctos; wolves, Canis lupus) and now perhaps fear humans more. We tested the fearfulness badgers demonstrated to audio playbacks of extant (dog) and extinct (bear and wolf) large carnivores, and humans, by assaying the suppression of foraging behavior. Hearing humans affected latency to feed, vigilance, foraging time, number of feeding visits, and number of badgers feeding. Hearing dogs and bears had far lesser effects on latency to feed, and hearing wolves had no effects. Our results indicate fear of humans evidently cannot substitute for the fear large carnivores inspire in mesocarnivores because humans are perceived as far more frightening, which we discuss in light of the recovery of large carnivores in human-dominated landscapes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it