Active cultural transmission of fitness-enhancing behavior can be seen as a costly strategy: one for which its evolutionary stability poses a Darwinian puzzle. In this article, we offer a biological market model of cultural transmission that substitutes or complements existing kin selection-based proposals for the evolution of cultural capacities. We demonstrate how a biological market can account for the evolution of teaching when individual learners are the exclusive focus of social learning. We also show how this biological market can affect (...) the dynamics of cumulative culture. The model works best when it is difficult to have access to the observation of the behavior without the help of the actor. However, in contrast to previous non-mathematical hypotheses for the evolution of teaching, we show how teaching evolves, even when innovations are insufficiently opaque and therefore vulnerable to acquisition by emulators via inadvertent transmission. Furthermore, teaching in a biological market is an important precondition for enhancing individual learning abilities. (shrink)

According to the working definition of the International Big History Association, ‘Big History seeks to understand the integrated history of the Cosmos, Earth, Life and Humanity, using the best available empirical evidence and scholarly methods’. In recent years Big History has been developing very fast indeed. Big History courses are taught in the schools and universities of several dozen countries. Hundreds of researchers are involved in studying and teaching Big History. The unique approach of Big History, the interdisciplinary genre of (...) history that deals with the grand narrative of 13.8 billion years, has opened up a vast amount of research agendas. Big History brings together constantly updated information from the scientific disciplines and merges it with the contemplative realms of philosophy and the humanities. It also provides a connection between the past, present, and future. Big History is a colossal and extremely heterogeneous field of research encompassing all the forms of existence and all timescales. Unsurprisingly, Big History may be presented in very different aspects and facets. In this volume the Big History is presented and discussed in three different ways. In its first part, Big History is explored in terms of methodology, theories of knowledge, as well as showcasing the personal approach of scholars to Big History. The second section comprises such articles that could clarify Big History's main trends and laws. The third part of this book explores the nature of teaching Big History as well as profiling a number of educational methods. This volume will be useful both for those who study interdisciplinary macroproblems and for specialists working in focused directions, as well as for those who are interested in evolutionary issues of Astrophysics, Geology, Biology, History, Anthropology, Linguistics and other areas of study. (shrink)

Over the last 40 years or so, there has been an explosion of cultural evolution research in anthropology and archaeology. In each discipline, cultural evolutionists investigate how interactions between individuals translate into group level patterns, with the aim of explaining the diachronic dynamics and diversity of cultural traits. However, while much attention has been given to deterministic processes, we contend that current evolutionary accounts of cultural change are limited because they do not adopt a systematic stochastic approach. First, we show (...) that, in contrast with the intense debates in ecology and population genetics, the importance of stochasticity in evolutionary processes has generated little discussion in the sciences of cultural evolution to date. Second, we speculate on the reasons, both ideological and methodological, why that should be so. Third, we highlight the inadequacy of genetically-inspired stochastic models in the context of cultural evolution modelling, and ask which fundamental stochastic processes might be more relevant to take up. We conclude that the field of cultural evolution would benefit from a stochastic revolution. For that to occur, stochastic models ought to be developed specifically for cultural data and not through a copy-pasting of neutral models from population genetics or ecology. (shrink)

Cultural evolution studies are characterized by the notion that culture evolves accordingly to broadly Darwinian principles. Yet how far the analogy between cultural and genetic evolution should be pushed is open to debate. Here, we examine a recent disagreement that concerns the extent to which cultural transmission should be considered a preservative mechanism allowing selection among different variants, or a transformative process in which individuals recreate variants each time they are transmitted. The latter is associated with the notion of “cultural (...) attraction”. This issue has generated much misunderstanding and confusion. We first clarify the respective positions, noting that there is in fact no substantive incompatibility between cultural attraction and standard cultural evolution approaches, beyond a difference in focus. Whether cultural transmission should be considered a preservative or reconstructive process is ultimately an empirical question, and we examine how both preservative and reconstructive cultural transmission has been studied in recent experimental research in cultural evolution. Finally, we discuss how the relative importance of preservative and reconstructive processes may depend on the granularity of analysis and the domain being studied. (shrink)

Human culture is uniquely complex compared to other species. This complexity stems from the accumulation of culture over time through high- and low-fidelity transmission and innovation. One possible reason for why humans retain and create culture, is our ability to modulate teaching strategies in order to foster learning and innovation. We argue that teaching is more diverse, flexible, and complex in humans than in other species. This particular characteristic of human teaching rather than teaching itself is one of the reasons (...) for human’s incredible capacity for cumulative culture. That is, humans unlike other species can signal to learners whether the information they are teaching can or cannot be modified. As a result teaching in humans can be used to support high or low fidelity transmission, innovation, and ultimately, cumulative culture. (shrink)

This paper begins by calling attention to a puzzling feature of our deep past: an apparent mis-match between morphological evolution in our lineage, including the expansion of our brain and neocortex, and changes in material culture. Three ideas might explain this mis-match. The apparent mis-match is an illusion: change in material culture is indeed driven by biological evolution, but of a kind difficult to identify in the fossil record; the mismatch is caused by the fact that material culture is sensitive (...) to the social and demographic environment, not just the native cognitive capacities of individual agents. Innovation and its uptake is more reliable in larger social worlds. The mis-match is made possible by adaptive phenotypic plasticity; in particular, cognitive plasticity. Just as material culture evolves through cumulative cultural learning, so too do cognitive skills, including ones which make innovations in, and the transmission of, material culture more efficient. This paper is targeted on the second of these ideas, and distinguishes three different versions of the view that increases in social scale support increases in the complexity of material culture. Those are: cultural selection is more efficient in larger social worlds; larger social worlds support more specialisation, which in turn supports a more complex material culture; cultural learning is more efficient in larger social worlds. The paper argues that the first two of these pathways are probably more important than the third in explaining otherwise puzzling features of the archaeological and ethnographic record. (shrink)

There has been much debate regarding when modern human cognition arose. It was previously thought that the technocomplexes and artifacts associated with a particular timeframe during the Upper Paleolithic could provide a proxy for identifying the signature of modern cognition. It now appears that this approach has underestimated the complexity of human behavior on a number of different levels. As the artifacts, once thought to be confined to Europe 40,000 years ago onwards, can now be found in other parts of (...) the world well before this date, especially in South Africa, this suggests that modern cognition arose well before this period. Moreover, the variability of the archaeological record from the time when anatomically modern humans appeared 200,000 years ago suggests cognitive factors alone are unable to explain the obvious unevenness. In this article, it will be demonstrated how neuro-cognition can be assimilated with population dynamics and the transmission of information between individuals and groups that can provide important insights as to the nature and origins of modern human cognition. (shrink)

Learning to use, make, and modify tools is key to our species’ success. Researchers have hypothesized that play with objects may have a foundational role in the ontogeny of tool use and, over evolutionary timescales, in cumulative technological innovation. Yet, there are few systematic studies investigating children’s interactions with objects outside the post-industrialized West. Here, we survey the ethnohistorical record to uncover cross-cultural trends regarding hunter-gatherer children’s use of objects during play and instrumental activities. Our dataset, consisting of 434 observations (...) of children’s toys and tools from 54 hunter-gatherer societies, reveals several salient trends: Most objects in our dataset are used in play. Children readily manufacture their own toys, such as dolls and shelters. Most of the objects that children interact with are constructed from multiple materials. Most of the objects in our dataset are full-sized or miniature versions of adult tools, reflecting learning for adult roles. Children also engage with objects related to child culture, primarily during play. Taken together, our findings show that hunter-gatherer children grow up playing, making, and learning with objects. (shrink)

Previous models of cultural evolution found that larger populations can better maintain complex technologies because they contain more highly skilled people whom others can imitate. These models, however, do not distinguish the effects of population size from population density or network size; a learner’s social network includes the entire population. Does population size remain important when populations are subdivided and networks are realistically small? I use a mathematical model to show that population size has little effect on equilibrium levels of (...) mean skill under a wide range of conditions. The effects of network size and transmission error rate usually overshadow that of population size. Population size can, however, affect the rate at which a population approaches equilibrium, by increasing the rate at which innovations arise. This effect is small unless innovation is very rare. Population size should predict technological complexity in the real world, then, only if technological evolution is a slow, innovation-limited process. Population density and “connectedness” have similar affects to population size, though density can also affect equilibrium skill. I discuss the results of this analysis in light of the current empirical debate. (shrink)

In the study reported here we examined the impact of population size and two proxies of risk of resource failure on the diversity and complexity of the food-getting toolkits of hunter–gatherers and small-scale food producers. We tested three hypotheses: the risk hypothesis, the population-size hypothesis, and a hypothesis derived from niche construction theory. Our analyses indicated that the toolkits of hunter–gatherers are more affected by risk than are the toolkits of food producers. They also showed that the toolkits of food (...) producers are more affected by population size than are the toolkits of hunter–gatherers. This pattern is inconsistent with the predictions of both the risk hypothesis and the population-size hypothesis. In contrast, it is consistent with the predictions of the niche construction hypothesis. Our results indicate that niche construction has affected the evolution of technology in small-scale societies and imply that niche construction must be taken into account when seeking to understand technological variation among food producers and the technological changes that occurred in association with the various transitions to farming that have occurred over the last 10,000 years. (shrink)