In this paper, the authors utilize phylogenetic methods to reconstruct the evolution of land tenure norms among 97 Austronesian societies. They coded these norms for each society as none (N), group (G), group-kin (K), and individual (I). After formulating various models of evolution through these various stages, they used Bayesian analysis to determine support for each. They conclude with remarks about this type of evolutionary phylogenetic research as a form of "virtual archeology."

In this paper, the authors utilize phylogenetic methods to reconstruct the evolution of land tenure norms among 97 Austronesian societies. They coded these norms for each society as none (N), group (G), group-kin (K), and individual (I). After formulating various models of evolution through these various stages, they used Bayesian analysis to determine support for each. They conclude with remarks about this type of evolutionary phylogenetic research as a form of "virtual archeology."

In this paper, the authors utilize phylogenetic methods to reconstruct the evolution of land tenure norms among 97 Austronesian societies. They coded these norms for each society as none (N), group (G), group-kin (K), and individual (I). After formulating various models of evolution through these various stages, they used Bayesian analysis to determine support for each. They conclude with remarks about this type of evolutionary phylogenetic research as a form of "virtual archeology."

In this paper, the authors utilize phylogenetic methods to reconstruct the evolution of land tenure norms among 97 Austronesian societies. They coded these norms for each society as none (N), group (G), group-kin (K), and individual (I). After formulating various models of evolution through these various stages, they used Bayesian analysis to determine support for each. They conclude with remarks about this type of evolutionary phylogenetic research as a form of "virtual archeology."

In this paper, the authors utilize phylogenetic methods to reconstruct the evolution of land tenure norms among 97 Austronesian societies. They coded these norms for each society as none (N), group (G), group-kin (K), and individual (I). After formulating various models of evolution through these various stages, they used Bayesian analysis to determine support for each. They conclude with remarks about this type of evolutionary phylogenetic research as a form of "virtual archeology."

In this paper, the authors utilize phylogenetic methods to reconstruct the evolution of land tenure norms among 97 Austronesian societies. They coded these norms for each society as none (N), group (G), group-kin (K), and individual (I). After formulating various models of evolution through these various stages, they used Bayesian analysis to determine support for each. They conclude with remarks about this type of evolutionary phylogenetic research as a form of "virtual archeology."

In this paper, the authors utilize phylogenetic methods to reconstruct the evolution of land tenure norms among 97 Austronesian societies. They coded these norms for each society as none (N), group (G), group-kin (K), and individual (I). After formulating various models of evolution through these various stages, they used Bayesian analysis to determine support for each. They conclude with remarks about this type of evolutionary phylogenetic research as a form of "virtual archeology."

In this paper, the authors utilize phylogenetic methods to reconstruct the evolution of land tenure norms among 97 Austronesian societies. They coded these norms for each society as none (N), group (G), group-kin (K), and individual (I). After formulating various models of evolution through these various stages, they used Bayesian analysis to determine support for each. They conclude with remarks about this type of evolutionary phylogenetic research as a form of "virtual archeology."

The researchers use phylogenetic methods to map out the evolutionary trajectories of land tenure norms across 97 Austronesian societies. The analysis suggests the relevance of vertical transmission in patterning land tenure norms, rather than horizontal transmission. It also strongly supports a model along a N(none)-I(individual)-G(group)-K(kin) pathway.

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.