Behavioral Endocrinology of Male Dispersal in Vervet Monkeys at Lake Nabugabo, Uganda
Bibliographic record
Abstract
Dispersal between social groups reduces risks of inbreeding and may provide individuals with reproductive opportunities. However, this movement may come with socio-ecological costs, such as risks of predation and starvation, loss of allies, kin support, and increased conspecific aggression. Dispersal strategies, such as the timing of movement and decisions on whether to transfer alone or in parallel with a peer may be associated with different costs and benefits between individuals. This research uses long-term demographic, behavioral, hormone, and ecological data to examine the triggers and consequences of 36 dispersal events from 29 male vervet monkeys (Chlorocebus pygerythrus) at Lake Nabugabo, Uganda. Dispersing adult males timed their transfer with the conception seasonality and improved their potential access to females by moving to a group with higher female-to-male sex ratio or by increasing their dominance rank. However, we argue that each transfer is unique to each individual and their own socio-ecological context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".