|Created: 05 Sep 2013||Modified: 23 Jun 2017||BibTeX Entry||RIS Citation|
Cultural Transmission of Structured Knowledge and Technological Complexity: Axelrod’s Model Extended
Cultural transmission models are coming to the fore in explaining increases in the Paleolithic toolkit richness and diversity. Analyses suggest that diversity increased due to relaxation of conformism, due to the effects of demographic expansion on cultural diversity, and the effects of extinction and recolonization in metapopulations. During the Paleolithic, however, technologies increase not only in terms of diversity but also in their complexity and interdependence. As Mesoudi and O’Brien (2008) have shown selection broadly favors social learning that is hierarchical and structured, rather than information which is piecemeal and independent. The addition of structured information acquisition potentially explains how the complexity of technology changes along with diversity. Here, we introduce a variant of Axelrod’s model of cultural differentiation, modified such that homophily and conformism refers to the content or “semantics” of traits, instead of simply their frequencies. We examine the conditions under which structured suites of traits develop and differentiate in the model, which can represent the chains of prerequisites, “background” information, and local specializations characteristic of real technology traditions. Our results point to ways in which we can build more comprehensive explanations of the archaeological record of the Paleolithic as well as other cases of technological change.
A prominent explanation for the sharp increase in cultural diversity and toolkit richness in the later Paleolithic has been that early Paleolithic hominids simply lacked the cognitive capacities of later humans (Klein 2000; Klein 2002; Wynn and Coolidge 2004). But as better data accumulate, and it becomes clear that anatomically modern H. sapiens and Neandertals are both responsible for complex “Upper Paleolithic” assemblages, and that diversity and richness increased in a patchwork manner over a long time span, the idea that biological differences can account for the “Upper Paleolithic Revolution” seems incorrect.
Changes in the mode, pattern, and demographic context of cultural transmission are another way that human “cognitive capacities” can change, however. In other words, instead of focusing upon the “hardware,” we might explore ways in which the explosion of diversity and toolkit richness in the later Paleolithic is a change in “software.”
One possibility is that population size affects the total amount of cultural diversity that can be “stored” in a population (Powell, Shennan, and Thomas 2009; Shennan 2000; Shennan 2001; Henrich 2004b).
Another possibility is that in a structured population of small groups (i.e., a metapopulation), local extinctions can result in the loss of innovations and diversity before it can spread throughout a network of populations and thus become entrenched (Premo 2012).
Clearly, these are not mutually exclusive ideas. The effective population size, both of local populations and a regional metapopulation, will affect how much cultural information and knowledge is “stored” and passed onto future generations.
Two authors have also suggested that a form of “conformist” transmission characterized Middle Paleolithic hominids, leading to assemblages of low diversity and long-lived variants (Gowlett 1996; Sharon 2009). Conformism is usually modeled as copy-most-frequent, and thus as frequency-dependent selection, but Axelrod’s model of cultural differentiation features “homophily,” the tendency of individuals to preferentially interact with those similar to oneself (Axelrod 1997). Homophily is another kind of “conservative” cultural transmission rule. Either or both may have been operative in past human societies.
Notably, conformism and homophily are orthogonal to demographic and social network models. Indeed, the cultural repertoire of real populations is undoubtedly a product of the interaction of demographic effects on transmission, the evolving social network at individual and metapopulation levels, the shifting modes of imitation and copying used by people in different contexts, and of course the selective value of the cultural information in the repertoire.
But this is still not a complete view of the components of cultural transmission. What’s missing is the content of cultural information itself, and how that content interacts with social learning in various use contexts (or niches). For example, some skills and information are prerequisite to other skills or knowledge. In the transmission sense of information (Bergstrom and Rosvall 2011), linked traits simply represent pleiotropy. But one way in which cultural transmission differs from genetic transmission is that social learning can easily be dependent not just upon the choice of individuals with whom to exchange information (i.e., assortative mating), but upon the content of the information itself. Boyd and Richerson long ago recognized such a process in their description of “direct bias” (Boyd and Richerson 1985), but optimality evaluation of alternative traits hardly exhausts the possible space of “content sensitive” cultural transmission rules.
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