Using Bayesian phylogenetic analysis, the authors ask: "Do cultural traits exhibit different histories of transmission?". They explore two competing models regarding Iranian tribal textile tradition. First, the "hierarchically integrated system hypothesis" emphasizes the importance of a core tradition and peripheral traits that are shared among contemporaneous populations. Second, the "multiple coherent units hypothesis" suggests that the groups of cultural traits have different transmission histories. The results show more support towards the "multiple coherent units hypothesis", specifically that pile-weave designs emerge as a cultural unit with a unique phylogenetic history compared to other textile characters.

Ikat and warp weaving techniques have a long history in Southeastern Asia and tend to be the most geographically widespread in the region. This researcher uses Bayesian and Neighbornet techniques to create models of phylogenetic descent and distribution of SE Asian weaving traditions. These findings do not support the theory of late Bronze Age Dong-Son descent.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

This article examines the relationship between craft specialization, technological complexity, the gendered division of labor, and trade. Seeking to understand the shift from women to men as primary weavers, the author finds that trade is a strong predictor but technological complexity of looms is not.

This article examines the relationship between craft specialization, technological complexity, the gendered division of labor, and trade. Seeking to understand the shift from women to men as primary weavers, the author finds that trade is a strong predictor but technological complexity of looms is not.

This chapter examines the variables that favor restrictive premarital sex norms. Findings indicate that subsistence economy, technology, population size, political integration, belief in a high god, and residence are all correlated with premarital sex norms.