Delineating connectivity and quality of peer–peer pre-pubescent rhesus macaque ( <i>Macaca mulatta</i> ) relationships, by examining coupled social behaviours
Bibliographic record
Abstract
Infant experiences have lifetime implications for individuals’ social competence. Therefore, lifelong trajectories can be informed by a nuanced understanding of who developing individuals connect with (i.e. connectivity) and how invested they are in those connections (i.e. quality). Though simple in premise, the practice of examining social connectivity and quality relies on a nuanced understanding of how individuals temporally shift their behavioural repertoire within, or across, partners. We measured peer–peer relationships throughout the first 3 years of life among 49 rhesus macaques ( Macaca mulatta ) in large outdoor-housed mixed-sex home groups. We recorded five social behaviours and built multiplex temporal networks. We examined the auto- and cross-correlations of these behaviours using a multivariate multiple response time series model to understand the behavioural dynamics of relationship connectivity and quality. We demonstrate known principles of relationship formation driven by pre-pubescents’ and peer partners’ traits (i.e. rank, sex, age, kinship). Coupled dynamics suggest that proximity was broadly associated with social dynamics (including aggression), while contact was associated with prosocial dynamics (excluding aggression). Directed behaviours were less associated with each other. These results highlight the dynamic nature of social development across multiple behaviours, underscoring how early social choices shape the formation, stability and maintenance of relationships.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".