Published papers

© 2019, The Author(s), under exclusive licence to Springer Nature Limited. The origins of religion and of complex societies represent evolutionary puzzles1–8. The ‘moralizing gods’ hypothesis offers a solution to both puzzles by proposing that belief in morally concerned supernatural agents culturally evolved to facilitate cooperation among strangers in large-scale societies9–13. Although previous research has suggested an association between the presence of moralizing gods and social complexity3,6,7,9–18, the relationship between the two is disputed9–13,19–24, and attempts to establish causality have been hampered by limitations in the availability of detailed global longitudinal data. To overcome these limitations, here we systematically coded records from 414 societies that span the past 10,000 years from 30 regions around the world, using 51 measures of social complexity and 4 measures of supernatural enforcement of morality. Our analyses not only confirm the association between moralizing gods and social complexity, but also reveal that moralizing gods follow—rather than precede—large increases in social complexity. Contrary to previous predictions9,12,16,18, powerful moralizing ‘big gods’ and prosocial supernatural punishment tend to appear only after the emergence of ‘megasocieties’ with populations of more than around one million people. Moralizing gods are not a prerequisite for the evolution of social complexity, but they may help to sustain and expand complex multi-ethnic empires after they have become established. By contrast, rituals that facilitate the standardization of religious traditions across large populations25,26 generally precede the appearance of moralizing gods. This suggests that ritual practices were more important than the particular content of religious belief to the initial rise of social complexity.

© 2016 American Psychological Association. Creativity research examines both the processes and products of creativity. An important avenue for analyzing creativity is by means of spontaneous improvisation, although there are major challenges to characterizing the products of improvisation because of their variable nature. A useful concept missing from the analysis of improvisation is the idea that the products of a corpus can be organized into a series of "style-types," where each type differs from others in certain key structural features. Clustering methods provide a reliable quantitative means of examining the organization of style-types within a diverse corpus of improvisations. To look at the utility of such methods, we examined a sample of 72 vocal melodic improvisations produced by novice improvisers. We first classified the melodies acoustically using a multidimensional musical-classification scheme, which coded the melodies for 19 distinct features of musical structure. We next employed multiple correspondence analysis (a dimensional reduction method) and k-means cluster analysis simultaneously, and obtained 3 relatively discrete clusters of improvisations. Stylistic analysis of these clusters revealed that they differed in key musical features related to phrase structure and rhythm. Cluster analyses provide a promising means of describing and analyzing the products of creativity, including variable structures like spontaneous improvisations.

© 2020 BY THE REGENTS OF THE UNIVERSITY OF CALIFORNIA ALL RIGHTS RESERVED. MANY FOUNDATIONAL QUESTIONS IN THE psychology of music require cross-cultural approaches, yet the vast majority of work in the field to date has been conducted with Western participants and Western music. For cross-cultural research to thrive, it will require collaboration between people from different disciplinary backgrounds, as well as strategies for overcoming differences in assumptions, methods, and terminology. This position paper surveys the current state of the field and offers a number of concrete recommendations focused on issues involving ethics, empirical methods, and definitions of "music" and "culture.".

Unfounded music copyright lawsuits inhibit musical creativity and waste millions of taxpayer dollars annually. Our aim was to develop and test simple quantitative methods in order to supplement traditional qualitative musicological analyses and improve the efficiency and transparency of music copyright lawsuits. We adapted automatic sequence alignment algorithms from computational biology to create a "percent melodic identity" (PMI) method that was initially developed to measure the cultural evolution of folk music from different cultures. This method automatically quantifies and visualizes the percentage of identical pitch classes shared between two melodic sequences. We applied the PMI method to a corpus of 20 pairs of melodies that had been the subject of legal decisions and that had previously been analyzed using automatic methods. We found that the PMI method was able to accurately predict 80% (16/20) of previous decisions, with PMIs below 50% usually resulting in decisions of no infringement (11/13 cases), and PMIs above 50% usually resulting in decisions of infringement (5/7 cases). Importantly, each of the four outlying cases could be explained by contextual factors not related to melodic similarity (e.g., lyrics, access). Our results provide promise for improving music copyright evaluation by supplementing traditional qualitative components with quantitative methods and visualization tools that are simple enough to be useful to juries, judges, and other non-musicologists.