DOMINANCE HIERARCHIES IN FEMALE MOUNTAIN GOATS: STABILITY, AGGRESSIVENESS AND DETERMINANTS OF RANK
Bibliographic record
Abstract
Abstract To investigate the importance of dominance relationships in the social organization of large mammals, I studied the aggressive behaviour of marked adult female mountain goats (Oreamnos americanus) during four years in west-central Alberta, Canada. Despite large group size, the 38-45 adult females in the population were organized in a strong and very stable linear hierarchy. Social rank was strongly related to age and did not decrease for the oldest females. The presence of a kid did not affect the aggressive behaviour of females, suggesting that aggressiveness probably did not evolve for offspring defense in mountain goats. Initiators won most encounters, except when the receiver was an older female. When age was accounted for, body mass, horn length, and body size were not related to female rank. A new measure of aggressiveness, controlling for the number of opportunities for interactions, revealed that aggressiveness towards younger adult females increased with both age and social rank. On the other hand, age and social rank did not affect aggressiveness towards other females of the same age or older. Goats interacted more often with individuals of similar ranks than with individuals that were distant in the dominance hierarchy. Social rank of adult daughters was not related to the social rank of mothers. Although central positions in a group may decrease predation risk, dominant females did not occupy central positions more often than subordinates. Because age was the main determinant of rank, the only effective way to increase social rank was to survive.
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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 | 0.001 | 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".