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Journal of Anthropological Research: vol. 65, no. 4, (dlps) 0521004.0065.403, http://hdl.handle.net/2027/spo.0521004.0065.403, This work is protected by copyright and may be linked to without seeking permission. Permission must be received for subsequent distribution in print or electronically. Please contact mpub-help@umich.edu for more information.

Journal of Anthropological Research: vol. 65, no. 4, (dlps) 0521004.0065.403, http://hdl.handle.net/2027/spo.0521004.0065.403, This work is protected by copyright and may be linked to without seeking permission. Permission must be received for subsequent distribution in print or electronically. Please contact mpub-help@umich.edu for more information.

Social network data are often constructed by incorporating reports from multiple individuals. However, it is not obvious how to reconcile discordant responses from individuals. There may be particular risks with multiply reported data if people’s responses reflect normative expectations—such as an expectation of balanced, reciprocal relationships. Here, we propose a probabilistic model that incorporates ties reported by multiple individuals to estimate the unobserved network structure. In addition to estimating a parameter for each reporter that is related to their tendency of over- or under-reporting relationships, the model explicitly incorporates a term for ‘mutuality’, the tendency to report ties in both directions involving the same alter. Our model’s algorithmic implementation is based on variational inference, which makes it efficient and scalable to large systems. We apply our model to data from a Nicaraguan community collected with a roster-based design and 75 Indian villages collected with a name-generator design. We observe strong evidence of ‘mutuality’ in both datasets, and find that this value varies by relationship type. Consequently, our model estimates networks with reciprocity values that are substantially different than those resulting from standard deterministic aggregation approaches, demonstrating the need to consider such issues when gathering, constructing, and analysing survey-based network data.

A hypothesis for the evolution of long post-reproductive lifespans in the human lineage involves asymmetries in relatedness between young immigrant females and the older females in their new groups. In these circumstances, inter-generational reproductive conflicts between younger and older females are predicted to resolve in favour of the younger females, who realize fewer inclusive fitness benefits from ceding reproduction to others. This conceptual model anticipates that immigrants to a community initially have few kin ties to others in the group, gradually showing greater relatedness to group members as they have descendants who remain with them in the group. We examine this prediction in a cross-cultural sample of communities, which vary in their sex-biased dispersal patterns and other aspects of social organization. Drawing on genealogical and demographic data, the analysis provides general but not comprehensive support for the prediction that average relatedness of immigrants to other group members increases as they age. In rare cases, natal members of the community also exhibit age-related increases in relatedness. We also find large variation in the proportion of female group members who are immigrants, beyond simple traditional considerations of patrilocality or matrilocality, which raises questions about the circumstances under which this hypothesis of female competition are met. We consider possible explanations for these heterogenous results, and we address methodological considerations that merit increased attention for research on kinship and reproductive conflict in human societies. This article is part of the theme issue 'The evolution of female-biased kinship in humans and other mammals'.