Re-evaluating the relationship between female social bonds and infant survival in wild baboons
Bibliographic record
Abstract
Over the past few decades studies have provided strong evidence that the robust links between the social environment, health, and survival found in humans also extend to non-human social animals. A number of these studies emphasize the early life origins of these effects. For example, in several social mammals, more socially engaged mothers have infants with higher rates of survival compared to less socially engaged mothers, suggesting that positive maternal social relationships causally improve offspring survival. Here we show that the relationship between infant survival and maternal sociality is confounded by previously underappreciated variation in female social behavior linked to changes in reproductive state and the presence of a live infant. Using data from a population of wild baboons living in the Amboseli basin of Kenya - a population where high levels of maternal sociality have previously been linked to improved infant survival - we find that infant- and reproductive state-dependent changes in female social behavior drive a statistically significant relationship between maternal sociality and infant survival. After accounting for these state-dependent changes in social behavior, maternal sociality is no longer positively associated with infant survival in this population. Our results emphasize the importance of considering multiple explanatory pathways-including third-variable effects-when studying the social determinants of health in natural populations.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| 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".