Youngblood Mason
Department of Psychology, The Graduate Center, City University of New York, New York, NY, USA.
Department of Biology, Queens College, City University of New York, Flushing, NY, USA.
R Soc Open Sci. 2019 Sep 25;6(9):191149. doi: 10.1098/rsos.191149. eCollection 2019 Sep.
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.
文化进化研究的基本问题之一是个体层面的过程如何放大以产生群体层面的模式。先前的音乐研究表明，基于频率的偏向（如从众和新奇）在不同领域和分析层面以不同方式推动大规模文化多样性。音乐采样是这个过程的理想研究模型，因为已知样本在合作艺术家之间进行文化传播，并且采样事件在在线数据库中有可靠记录。本研究的目的是利用一个跨越三十年的采样事件纵向数据集，确定基于频率的偏向是否在音乐采样传统的文化传播中发挥了作用。首先，我们评估流行样本的更替率是否与中性进化下预期的不同。接下来，我们在近似贝叶斯计算框架中使用基于主体的模拟，以推断基于频率的偏向水平可能产生了观察到的数据。尽管有新奇偏向的轶事证据，但我们发现群体层面的采样模式最符合从众偏向。我们最后讨论了反主导信号如何使新奇偏向的个别案例与群体层面的从众相一致。
