Patterns of Male–Female and Male–Male Social Associations Within Rwenzori Angolan Colobus Monkey (Colobus angolensis ruwenzorii) Core Units
Bibliographic record
Abstract
Abstract Understanding the evolution of multilevel societies is important for elucidating our own social evolution. The Rwenzori Angolan colobus (Colobus angolensis ruwenzorii) multilevel society is unique in its high prevalence of multi-male/multi-female core units and rare occurrence of all-male units. However, little is known about male-male social behaviour within multi-male core units or how male-female bonds are distributed among the males. We used social network analysis to examine spatial-proximity networks for identifiable colobus within eight multi-male/multi-female core units at Nabugabo, Uganda. Over a 12-month period, we found variation in the structure of male-female relationships, showing one of three patterns; (1) one male was preferred by females while others remained peripheral to the network (N = 3 units), (2) males and females were divided into social clusters where each male monopolized the social relationships of two to three females (N = 2 units), (3) all males invested equally in their associations with females and more significantly in each other (N = 3 units). Importantly, each of these social structures showed evidence of strong male-male bonds. Pairing these data with co-residency and parallel dispersal data from five subsequent years showed that males with more equitable patterns of proximity to females stayed together significantly longer and transferred together more in the future. We conclude that the variation in social network structure between core units reflects different strategies used by males to access the benefits of group-living and defend resources, mates, and offspring. Our study demonstrates that male Rwenzori colobus form lasting bonds that can transcend multiple dispersals between units.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".