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.

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.

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.

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.

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.

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.

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.

This study examines the relationship between equality and democracy, focusing on social stratification and political participation as the primary measures. Results suggest that equality strengthens some aspects of democracy, but several other factors such as industrialization are involved in the relationship.

This study uses Bayesian phylogenetic regression modelling across 131 largely non-industrial societies to test how variation of punishment is impacted by social, economic, and political organization. The authors focus on the presence of norm violations and types of punishments, and explores their relationships. The norm violations include adultery, rape, religious violations, food violations, and war cowardice. While the types of punishment are reputational, material, physical, or education. This study suggests a hypothesis for each type of punishment in relation to socioecological variables.