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.

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.

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.

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.

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.

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.

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.

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.