How Cultural Transmission Through Objects Impacts Inferences About Cultural Evolution

Journal of Archaeological Method and Theory https://doi.org/10.1007/s10816-022-09599-x How Cultural Transmission Through Objects Impacts Inferences About Cultural Evolution Enrico R. Crema1 · Eugenio Bortolini2 · Mark Lake3 Accepted: 6 December 2022 © The Author(s) 2023 Abstract The cross-fertilisation between biological and cultural evolution has led to an extensive borrowing of key concepts, theories, and statistical methods for studying temporal variation in the frequency of cultural variants. Archaeologists have been among the front-runners of those engaging with this endeavour, and the last 2 decades have seen a number of case studies where modes of social learning were inferred from the changing frequencies of artefacts. Here, we employ a simulation model to review and examine under-discussed assumptions shared by many of these applications on the nature of what constitutes the ‘population’ under study. We specifically ask (1) whether cultural transmission via ‘objects’ (i.e. public manifestations of cultural traits) generates distinct patterns from those expected from direct transmission between individuals and (2) whether basing inference on the frequency of objects rather than on the frequency of mental representations underlying the production of those objects may lead to biased interpretations. Our results show that the rate at which ideational cultural traits are embedded in objects, and shared as such, has a measurable impact on how we infer cultural transmission processes when analysing frequency-based archaeological data. At the same time, when cultural transmission is entirely mediated by the material representation of ideas, we argue that copying error should be interpreted as a two-step process which may occur in either one or both of embedding information in objects and retrieving it from them. Keywords Cultural evolution · Cultural transmission · Object-mediated transmission · Encoding/decoding error · Neutral evolution · Frequency data · Cultural attraction theory * Mark Lake Extended author information available on the last page of the article 13 Vol.:(0123456789) E. R. Crema et al. Introduction Time–frequency analyses of cultural data have long been a central theme in archaeological research, with contributions to issues pertaining to the construction of relative chronologies, and inferences on patterns of social learning, community and population structure, and identity. The rise and fall of cultural variants are ultimately the aggregate outcome of many individual decision-making processes, and thus, it is tempting to ask whether one can infer those processes, as well as the factors conditioning them, by analysing changes in the relative frequencies of discrete variants of a single cultural trait through time. Mathematical models of cultural transmission pioneered in the early 1980s by scholars such as Cavalli-Sforza, Feldman, Richerson, and Boyd (Boyd & Richerson, 1985; Cavalli-Sforza & Feldman, 1981) provided the foundations for such an endeavour. Given a putative social learning process, these formal models can make qualitative and quantitative predictions of how frequencies of cultural variants are expected to change over time. Forty years on, the now mature field of cultural evolutionary studies has considerably expanded its suite of transmission models (Kendal et al., 2018), but most importantly, it has been increasingly testing them against empirical evidence through experimental and observational studies (see Creanza et al., 2017; Mesoudi, 2017 for a review). Observational studies have, in particular, witnessed a transition from earlier applications where inferential tools were directly borrowed and adapted from population genetics (Neiman, 1995; Steele et al., 2010) to the development of tailored methods designed to handle the specific challenges posed by cultural evolution (Acerbi & Bentley, 2014; Bentley & Shennan, 2003; Bentley et al., 2011; Crema et al., 2016; Kandler & Crema, 2019; Kandler & Shennan, 2013; Nakamura et al., 2019; O’Dwyer & Kandler, 2017). The analysis of cultural frequency data arguably represents one of the best examples of this research trend. Early applications aimed to determine whether observed cultural diversity deviates from the expectations of an unbiased transmission process, whereby the probability of copying a cultural variant is simply dictated by its relative frequency in the population, and hence, changes in frequencies are solely dictated by the rate of innovation and random drift (i.e. the cumulative effect of these processes over time or geographic distance) (Bentley & Shennan, 2003; Bentley et al., 2004; Neiman, 1995; Steele et al., 2010). The methodological and theoretical insight underpinning this approach is the neutral theory of molecular evolution (Kimura, 1968), adapted to the investigation of cultural data by replacing alleles with cultural variants and employing haploid versions of different mathematical models (Neiman, 1995, see Kandler & Crema, 2019 for a review). However, students of cultural transmission must consider a wider range of alternative hypotheses and mechanisms than neutral evolution (unbiased transmission) versus selection. For this reason, there has been a substantial effort to develop inferential tools capable of determining the goodness-of-fit of other modes of cultural transmission (also known as social learning strategies, see Laland, 2004), including conformist and anti-conformist biases, pro-novelty bias, and attraction bias (Acerbi & Bentley, 2014; Crema et al., 2016; O’Dwyer & Kandler, 2017). These new statistical techniques have been applied to a wide range of cultural data sets, including baby 13 How Cultural Transmission Through Objects Impacts Inferences… names (Bentley et al., 2004), colour terms (Acerbi & Bentley, 2014), bitcoins (ElBahrawy et al., 2017), and music samples (Youngblood, 2019). A substantial proportion of case studies also concerns archaeological datasets. In fact, Neiman’s seminal work (Neiman, 1995), which first introduced the idea of borrowing concepts from the neutral theory of molecular evolution, aimed to investigate the stylistic variation of an archaeological dataset. This was followed by a small but steadily increasing number of similar studies over the last 20 years (Crema et al., 2014, 2016; Kohler et al., 2004; Lipo, 2001; Romanowska et al., 2021; Shennan & Wilkinson, 2001; Steele et al., 2010), mostly focused on (but not limited to) the study of ceramic assemblages and actively devoted to methodological development in this realm. Indeed, some of the most recent and advanced inferential techniques such as the use of progeny distributions (Bentley & Shennan, 2003) or approximate Bayesian computation (Crema et al., 2014; Kandler & Shennan, 2015) were first developed in the context of these archaeological applications. Archaeological case studies, however, have also highlighted some distinctive theoretical and methodolo (...truncated)