In this study, the authors examine pathways to social inequality, specifically social class hierarchy, in 408 non-industrial societies. In a path model, they find social class hierarchy to be directly associated with increased population size, intensive agriculture and large animal husbandry, real property inheritance (unigeniture) and hereditary political succession, with an overall R-squared of 0.45. They conclude that a complex web of effects consisting of environmental variables, mediated by resource intensification, wealth transmission variables, and population size all shape social inequality.

This study asks the following research questions: What are the dynamics of land ownership norms over time? Do these changes follow predetermined trajectories? The authors utilize biogeographical and evolutionary analyses to explore temporal and spatial patterns in land ownership norms within a sample of 73 Bantu societies. For the first component of the research, they test three prominent hypotheses regarding evolutionary trajectories: rectilinear, unilinear, and shift without restriction. For the second component, they use a multi-model inference approach to evaluate three hypotheses regarding the possible spatial patterns of land ownership. The results show evidence for the unilinear trajectory in type, but not with a consistent decrease in group ownership in size. Land ownership is more likely in areas with neighboring landowners and predictable resource productivity, while subsistence type is not significantly correlated with type of land ownership.

The researchers, using principal component analysis, generalized additive models across 12 agriculture origin locations, and a model predicting hunter-gatherer population density, evaluate hindcasted population density trends to suggest predictors of the development of agriculture. Using domestication as an indicator of agriculture, they test 3 competing hypotheses regarding agriculture development. Their results are consistent with the "surplus" hypothesis, indicating that agriculture arose as population densities increased along with environmental capabilities.

In this article, the authors seek to investigate why some societies reject agriculture despite its many benefits. By modeling data regarding ecological fitness and cultural transmission, the authors found predictors for the degree to which a society relies on agriculture. The authors conclude that the degree of fitness a local environment had for early domesticates as well as the degree of contact with neighboring societies strongly predicts levels of dependence on agriculture.

Is grammatical complexity shaped by sociodemographic and sociolinguistic factors? The previously accepted "linguistic niche hypothesis" claims that with an increased number of nonnative speakers in a social group (high exotericity), grammatic complexity decreases; on the other hand, grammatical complexity increases amongst isolated linguistic communities (low exotericity). Through the use of spatiophylogenetic modelling of 1314 languages, the authors of this study do not find adequate evidence to support the linguistic niche hypothesis. Instead, they suggest that linguistic complexity is better predicted by phylogeny and geographic contiguity.

Using multiple logistic regression, the researchers compare the relative strength of predictors of land ownership across 102 societies. The analysis finds significant predictive power in factors such as neighbors' property system, population density, and geography.

In this article, the authors seek to determine cross-culturally valid predictors of dominant types of human subsistence around the world. They did this by formulating multiple models that incorporate different combinations of environmental, geographic, and social factors. These models were then used to test various hypotheses posed throughout the anthropological literature surrounding factors that determine dominant subsistence strategies.

The article discusses the role of land ownership in natural resource management and social-ecological resilience, and explores the factors that determine ownership norms in human societies. The study tests long-standing theories from ecology, economics, and anthropology regarding the potential drivers of land ownership, including resource defensibility, subsistence strategies, population pressure, political complexity, and cultural transmission mechanisms. Using cultural and environmental data from 102 societies, the study found an increased probability of land ownership in mountainous environments and societies with higher population densities. The study also found support for the idea that neighboring societies might influence land ownership. However, there was less support for variables associated with subsistence strategies and political complexity.

Researchers investigated further into why and how humans speak so many languages across the globe, and why they are spread out unevenly. Using two different path analyses, a Stationary Path analysis and a GWPath, researchers tested the effect of eight different factors on language diversity. Out of the eight variables (river density, topographic complexity, ecoregion richness, temperature and precipitation constancy, climate change velocity, population density, and carrying capacity with group size limits), population density, carrying capacity with group size limit, and ecoregion richness had the strongest direct effects. Overall, the study revealed the role of multiple different mechanisms in shaping language richness patterns. The GWPath showed that not only does the most important predictor of language diversity vary over space, but predictors can also vary in the direction of their effects in different regions. They conclude that there is no universal predictor of language richness.

The authors examine multiple ecological variables as possible predictors of language diversity in North America using path analysis, mechanistic simulation modelling, and geographically weighted regression. They conclude that many of the variables do not predict language diversity, but rather are mediated by population density. The authors also find that the variables' ability to predict is not universal across the continent, but rather more regional.