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Neutral evolution assumes that there are no selective forces distinguishingdifferent variants in a population. Despite this striking assumption, manyrecent studies have sought to assess whether neutrality can provide a gooddescription of different episodes of cultural change. One approach has been totest whether neutral predictions are consistent with observed progenydistributions, recording the number of variants that have produced a givennumber of new instances within a specified time interval: a classic example isthe distribution of baby names. Using an overlapping generations model we showthat these distributions consist of two phases: a power law phase with aconstant exponent of -3/2, followed by an exponential cut-off for variants withvery large numbers of progeny. Maximum likelihood estimations of the modelparameters provide a direct way to establish whether observed empiricalpatterns are consistent with neutral evolution. We apply our approach to acomplete data set of baby names from Australia. Crucially we show that analysesbased on only the most popular variants, as is often the case in studies ofcultural evolution, can provide misleading evidence for underlying transmissionhypotheses. While neutrality provides a plausible description of progenydistributions of abundant variants, rare variants deviate from neutrality.Further, we develop a simulation framework that allows for the detection ofalternative cultural transmission processes. We show that anti-novelty bias isable to replicate the complete progeny distribution of the Australian data set.

Inferring processes of cultural transmission: the critical role of rare variants in distinguishing neutrality from novelty biases