Scalar social dynamics in female vervet monkey cohorts
Bibliographic record
Abstract
Primate social life and behaviour is contingent on a number of levels: phylogenetic, functional and proximate. Although this contingency is recognized by socioecological theory, variability in behaviour is still commonly viewed as 'noise' around a central tendency, rather than as a source of information. An alternative view is that selection has acted on social reaction norms that encompass demographic variation both between and within populations and demes. Here, using data from vervet monkeys (Chlorocebus aethiops pygerythrus), we illustrate how this alternative approach can provide a more nuanced account of social structure and its relation to contingent events at the ecological and demographic levels. Female vervets in our South African study population live in large groups, where they experience demographic stress and increased levels of feeding competition relative to an East African population in Amboseli, Kenya. Females in the South African population did not respond to this stress by intensifying competition for high-value grooming partners to help alleviate the effects of this stress, did not show the expected rank-related patterns of grooming, nor did they show any spatial association with their preferred grooming partners. Increased group size therefore resulted in a reorganization of female social engagement that was both qualitatively and quantitatively different to that seen elsewhere, and suggests that female vervets possess the flexibility to shift to alternative patterns of social engagement in response to contingent ecological and demographic conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".