How is the evolution of language shaped by speaker population size? Through comparative data analyses of 153 language pairs from the Austronesian, Indo-European, and Niger-Congo language families, the authors find that the influence of population size on language evolution is not the same in the three language families. Only in Indo-European languages did a smaller population size of language-speakers significantly predict more word loss.

How do subsystems of language evolve over time? It is commonly assumed that grammatical changes of language are slower than vocabulary changes. Using a Dirichlet process mixture model to analyze rates of language evolution in 81 Austronesian languages, the authors find that to the contrary, the grammatical features of language tend to change at a faster rate than basic vocabulary. Furthermore, their results show that grammatical features have higher rates of homoplasy, more frequent contact-induced change, and less deliberate differentiation than basic vocabulary.

Using linguistic trees as models of population history in combination with ethnographic data on kinship, the authors of the present study reconstruct post-marital residence rules of early Austronesian societies. Analyses include a Markov-chain Monte Carlo comparative method implemented in a Bayesian phylogenetic framework.

Population size is generally assumed to play a pivotal role in the evolution of languages and cultures, but the expected patterns and potential mechanisms of change are unsettled. Theoretical models are limited by this uncertainty because they require making prior assumptions about language evolution. Using a sample of 20 Polynesian languages, authors test the effect of population size on the gain, loss, and total change of basic vocabulary words.

A central issue in anthropology is the process through which political organization (sometimes referred to as cultural complexity) evolves: competing models typically argue for either incremental increases in complexity or larger, non-sequential increases in complexity. Here, the authors evaluate six different models of political evolution, utilizing a phylogenetic approach to analyze the evolution of 84 Austronesian-speaking societies.

Using phylogenetic modeling, the researchers test hypotheses for different sequences of political complexity among South-East Asian and Pacific Austronesian-speaking cultures. The research adds to an existing debate between sequential, incremental political evolution models and non-sequential models with larger increases in complexity. The results suggest support for a more sequential unilinear model.

How and when did Bantu populations expand through sub-Saharan Africa? Using phylogeographic analyses, the authors test four main hypotheses which aim to explain the route that the Bantu took as well as the date of expansion. The results suggest that Bantu populations migrated through the Central African rainforest around 4,400 years ago.

Using data on 25 ethnolinguistic groups in the Austronesian language family, this study asks: does cooperation in games vary with socio-ecological differences across cultural groups? The authors suggest that cultural groups that cooperate in subsistence, tend to have intergroup conflict and less intragroup conflict, and are less socially stratified are more likely to play cooperative games compared to other groups. While the results support the first three hypotheses, there is insufficient data to support the fourth. The authors conclude that games serve as training ground for group norms and values.

The authors investigate whether moralizing high gods and, more generally, supernatural punishment precede, sustain, or follow political complexity. The cultural traits at hand are mapped onto phylogenetic trees representing the descent and relatedness of 96 Austronesian cultures.

This study seeks to evaluate the degree to which classical kinship models are able to capture variation in kinship terminology. Following a description of the classical typologies of kinship, the authors use statistical approaches and a new database, Kinbank, to assess the internal coherence of these typologies; they find that these typologies are not necessarily accurate predictors of kinship terms across cultures. In addition, this analysis showed that the use of one sort of kinship typology for one generation may only weakly indicate its use in an adjacent generation. The authors set out to try and identify new typologies using statistical modeling based on the single-generation kinship terms of 306 languages. They successfully identify 9 clusters of kinship terms for just one generation alone, indicating that kinship terminology is much more diverse than previously thought. They conclude kinship typology and variation in kinship terminology needs to be investigated more thoroughly.