Individual, Group, and Environmental Influences on Helping Behavior in a Social Carnivore
Bibliographic record
Abstract
Abstract Variation in group composition and environment can affect helping behavior in cooperative breeders. Understanding of how group size, traits of individuals within groups, food abundance, and predation risk simultaneously influence helping behavior is limited. We evaluated pup‐guarding behavior in gray wolves (Canis lupus) to assess how differences in individuals, groups, and environment affect helping behavior. We used data from 92GPS‐collared wolves in North America (2001–2012) to estimate individual pup‐guarding rates. Individuals in groups with low helper‐to‐pup ratios spent more time guarding young than those in groups with more helpers, an indication of load‐lightening. Female helpers guarded more than male helpers, but this relationship weakened as pups grew. Subset analyses including data on helper age and wolf and prey density showed such factors did not significantly influence pup‐guarding rates. We show that characteristics of individuals and groups have strong influences on pup‐guarding behavior in gray wolves, but environmental factors such as food abundance and predation risk from conspecifics were not influential.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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 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".