<p>Music is greatly underappreciated in the scope of cross-cultural analysis. This is due in part to methodological problems plaguing recent comparative approaches, and modern ethnomusicology’s stance against cross-cultural analysis. Language, on the other hand, has a long history of cross-cultural study and recent advances in quantitative techniques, borrowed mostly from biology, have put language at the forefront of studying population prehistory from a cultural perspective. Chapter 2 of this thesis presents a novel quantitative approach to studying cross-cultural musical diversity based on the AMOVA methodology borrowed from population genetics. This method allows researchers to quantify the amount of variability found between as well as within populations, and gives us a measure of population-level divergence that accounts for intra-population variability. Our major finding is that the vast majority of musical variability (~98%) is found within populations rather than between. This approach solves many of the quantitative issues with the original Cantometrics approach, and is widely applicable to the analysis of many domains of culture. Aside from methodological issues a major open question is whether music has the requisite time-depth to answer questions about recent human pre-history. Chapter 3 focuses on addressing this question generally, and more specifically investigating which musical features trace population history most effectively. Using a corpus of songs from 9 Taiwanese aboriginal tribes and quantitative methods from chapter 2, we show that features related to song structure are correlated with mitochondrial DNA data from the same populations, while features of singing style are not. Both the quantitative methods and provisional support for music’s time depth presented here will hopefully usher in a new era of comparative musicology and provide scholars of pre-history with an additional tool to answer unresolved questions.</p> / Master of Science (MSc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/10976 |
| Date | 10 1900 |
| Creators | Rzeszutek, Tom I. |
| Contributors | Brown, Steven, Psychology |
| Source Sets | McMaster University |
| Detected Language | English |
| Type | thesis |
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