The Global Jukebox: A public database of performing arts and culture

Abstract

Standardized cross-cultural databases of the arts are critical to a balanced scientific understanding of the performing arts, and their role in other domains of human society. This paper introduces the Global Jukebox as a resource for comparative and cross-cultural study of the performing arts and culture. The Global Jukebox adds an extensive and detailed global database of the performing arts that enlarges our understanding of human cultural diversity. Initially prototyped by Alan Lomax in the 1980s, its core is the Cantometrics dataset, encompassing standardized codings on 37 aspects of musical style for 5,776 traditional songs from 1,026 societies. The Cantometrics dataset has been cleaned and checked for reliability and accuracy, and includes a full coding guide with audio training examples (https://theglobaljukebox.org/?songsofearth). Also being released are seven additional datasets coding and describing instrumentation, conversation, popular music, vowel and consonant placement, breath management, social factors, and societies. For the first time, all digitized Global Jukebox data are being made available in open-access, downloadable format (https://github.com/theglobaljukebox), linked with streaming audio recordings (theglobaljukebox.org) to the maximum extent allowed while respecting copyright and the wishes of culture-bearers. The data are cross-indexed with the Database of Peoples, Languages, and Cultures (D-PLACE) to allow researchers to test hypotheses about worldwide coevolution of aesthetic patterns and traditions. As an example, we analyze the global relationship between song style and societal complexity, showing that they are robustly related, in contrast to previous critiques claiming that these proposed relationships were an artifact of autocorrelation (though causal mechanisms remain unresolved).

Global musical diversity is largely independent of linguistic and genetic histories

“…For example, virtuosic accompanied solo singing may have spread along the Bronze Age trade networks and the Silk Routes in a neutral manner accompanying trade and other cultural exchange, and/or in a functional manner signalling and validating powerful hierarchies and the complex division of labour required to sustain large-scale trade networks (Lomax, 1968;Savage et al, 2021) as has been proposed for other aspects of culture such as religion (Norenzayan et al, 2016;Turchin et al, 2022). A reanalysis of proposed correlations between musical style and social structure supports Lomax's hypothesis of functional coevolution (Wood et al, 2022). Future analyses directly comparing music, social structure, language, genes, and geography will be needed to explain causal mechanisms.…”

“…A practical concern might be that the three datasets are not comparable, and therefore observing no relationship is expected. We believe this is not the case for two reasons: 1) previous studies have confirmed that it is possible to capture significant correlations between cultural and/or genetic data using the same types of data sources used here (Barbieri et al, 2022;Brown et al, 2014;Wood et al, 2022); and 2) our spatial autocorrelation analysis (Fig.…”

“…Global comparisons were not previously possible because detailed public data on cross-cultural musical diversity, genetic similarity, and language history were not available. This paper leverages new global databases of musical, genetic, and linguistic data (Barbieri et al, 2022;Bouckaert et al, 2022;Wood et al, 2022), to directly compare these three domains on a global scale.…”

“…The coding scheme and first batch of several thousands of coded songs were first debuted in Lomax's (1968) landmark book "Folk Song Style and Culture" and updated with thousands more songs over the subsequent decades. Most songs in the Global Jukebox database were coded by Lomax or Grauer themselves, and they have been recently validated for inter-rater reliability (mean κ =0.54) and accuracy (approximately 0.4-1% rate of unambiguous coding/data entry errors; Wood et al, 2022). The 37 variables vary substantially in reliability, from chance levels (e.g., nasality [Line 37]) to near-perfect (e.g., musical organization of the vocal part [Line 4] κ =0.94 / 89% agreement; Wood et al, 2022).…”

“…Most songs in the Global Jukebox database were coded by Lomax or Grauer themselves, and they have been recently validated for inter-rater reliability (mean κ =0.54) and accuracy (approximately 0.4-1% rate of unambiguous coding/data entry errors; Wood et al, 2022). The 37 variables vary substantially in reliability, from chance levels (e.g., nasality [Line 37]) to near-perfect (e.g., musical organization of the vocal part [Line 4] κ =0.94 / 89% agreement; Wood et al, 2022). Our robustness analyses removing low-reliability variables (Table S10) suggests that such variation does not affect our main results.…”