Temporal patterns in the social network of core units in Rwenzori Angolan colobus monkeys: effects of food availability and inter-unit dispersal
Bibliographic record
Abstract
Multi-level societies are complex social systems where basic core units associate in a hierarchical manner, allowing animals to adjust group size in response to local conditions. Each tier of multi-level societies may have evolved under different selective pressures and understanding the effect of temporal variation in these pressures may help determine why these types of social systems form. Our goal was to examine the degree of temporal variability in inter-unit associations in a multi-level society of Rwenzori Angolan colobus monkey (Colobus angolensis ruwenzorii), and to determine whether social or ecological factors correlated with association patterns. Using social network analyses, we described the association patterns of 12-13 core units over 21-months and investigated the effect of changes in rainfall, food availability, and inter-unit dispersals. We found that core unit networks were denser and more clustered when fruit was abundant, likely due to reduced food competition. Male dispersals also occurred more at these times, suggesting that greater band cohesion allowed males to prospect for dispersal opportunities. Within the band, we observed the formation of an all-male unit and the transfer of one core unit between clans. Our findings highlight how ecological conditions can influence association patterns, interunit relationships, and ultimately social organization.
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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".