Abstract
One of the fundamental questions of cultural evolutionary research is how individual-level processes scale up to generate population-level patterns. Previous studies in music have revealed that frequency-based bias (e.g. conformity and novelty) drives large-scale cultural diversity in different ways across domains and levels of analysis. Music sampling is an ideal research model for this process because samples are known to be culturally transmitted between collaborating artists, and sampling events are reliably documented in online databases. The aim of the current study was to determine whether frequency-based bias has played a role in the cultural transmission of music sampling traditions, using a longitudinal dataset of sampling events across three decades. Firstly, we assessed whether turn-over rates of popular samples differ from those expected under neutral evolution. Next, we used agent-based simulations in an approximate Bayesian computation framework to infer what level of frequency-based bias likely generated the observed data. Despite anecdotal evidence of novelty bias, we found that sampling patterns at the population-level are most consistent with conformity bias. We conclude with a discussion of how counter-dominance signalling may reconcile individual cases of novelty bias with population-level conformity.
Highlights
As Darwinian approaches are increasingly incorporated into modern musicology [1], researchers have begun to investigate how transmission biases shape the cultural evolution of music [2,3,4,5,6]
There is some evidence that dissonant intervals in Western classical music are subject to novelty bias [19], rhythms in Japanese enka music are subject to conformity bias [19], and popular music at the level of albums [15] and artists [20] is subject to random copying
By applying simulation-based methods to three decades of sampling events, we have provided evidence that conformity bias plays an important role in the cultural transmission of music sampling traditions
Summary
As Darwinian approaches are increasingly incorporated into modern musicology [1], researchers have begun to investigate how transmission biases shape the cultural evolution of music [2,3,4,5,6]. In the last several decades, researchers have begun to explore how these kinds of transmission 2 processes can be inferred from large-scale cultural datasets This ‘meme’s eye view’ approach [12], originally pioneered by archaeologists studying ceramics [13,14], has since been applied to dog breeds [15], cooking ingredients [16], and baby names [17]. In music, this approach has revealed that frequency-based biases like conformity and novelty, in which the probability of adopting a variant disproportionately depends on its commonness or rarity [18], vary across domains and levels of analysis. There is some evidence that dissonant intervals in Western classical music are subject to novelty bias [19], rhythms in Japanese enka music are subject to conformity bias [19], and popular music at the level of albums [15] and artists [20] is subject to random copying.
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