Knowledge Transmission: The Social Origin of Information and Cultural Evolution

This paper summarizes, contrasts, and reviews recent accounts of cultural evolution in our species offered by Cecilia Heyes in Cognitive Gadgets, Kevin Laland in Darwin’s Unfinished Symphony, and Michael Tomasello in Becoming Human. Our critical discussion focuses on the authors’ accounts of social learning, and the relationship each hypothesizes between cultural evolutionary and biological evolutionary processes. We find that both Laland and Tomasello seek to explain cultural evolution in humans as reliant upon processes of joint attention and shared intentionality (the development of which is largely the focus of Tomasello’s book). Heyes’ account of social learning, in which no particular role is assigned to human intersubjectivity and the same basic associative learning mechanisms of nonsocial learning are also invoked to explain social learning, stands apart. As to the relation of cultural and biological evolution, Laland offers readers a thorough account of the two with detailed analyses of social learning across various non-primate species, and uniquely, among these authors, attends to the influence of genes on social learning. For his part, Tomasello provides readers with a richly detailed experimental accounting of human-unique forms of social learning using Great Apes as points of contrast.

Recent theoretical work on the processes of cultural evolution helps to provide a clearer picture of the relationship between genetic and cultural influences on human behavior. The theory uses methods borrowed from evolutionary biology to study the unique properties of culture, but in a framework that permits a direct analysis of how genes and culture interact. The different scholars contributing to this program of research have rather different hypotheses regarding the relative importance of the processes that operate to cause cultural evolution. Some human sociobiologists propose that cultural evolution is very strongly constrained by the decision‐making of individuals. If so, human behavior can in principle be predicted rather directly from considerations of genetic fitness maximization. We are more impressed by the dynamic complexities introduced by a second system of inheritance. The difference between these hypotheses turns on the extent to which information is costly to acquire. When it is...

Culture consists of behavior. The units are practices shared by members of a group and acquired as a result of membership in the group. Although it is common to define the units of culture as abstractions, such as culturgens or memes, these abstractions in no way help to explain a group’s practices. Instead, they only direct research away from the context and consequences that result in transmission of a practice from one group member to another. If culture is to be described as an evolutionary process, one must have a sufficiently general definition of “evolutionary process” to allow genetic evolution and cultural evolution to be examples. This may be accomplished by defining an evolutionary process as composed of variation (within a pool of replicators), transmission (by copying), and selection (by differential transmission). The replicators of cultural evolution are practices, which are units of operant behavior (i.e., behavior under control of consequences and context). Practices are transmitted from individual to individual by imitation and instruction. Instruction may be understood with the concept of a rule, which is a verbal discriminative stimulus (i.e., a verbally created context). Instruction consists of rule-giving, which results in rule-following on the part of the instructee. New rules come into a culture frequently as a result of rule-making, the generation of new rules on the basis of non-social stimuli. Selection in cultural evolution occurs because imitation and instruction of competing practices have differential consequences in the long run, consequences that impact reproductive potential. Since such long-term consequences have little effect on behavior, an adaptive practice (i.e., one that pays in the long run, called “self-control”) is strengthened in the short-term by social reinforcers delivered by rule-givers. A behavioral analysis focuses on environmental events that are observable and, so, susceptible to research. The postulating of fictitious inner entities, whether they be memes, “devices,” or “modules,” only impedes understanding of culture and cultural evolution. Natural selection, because it is short-sighted and opportunistic, may be expected to produce mechanisms that aid and abet valuable behavioral functions. The key to understanding cultural evolution lies in understanding practices in the light of their environmental contexts and short- and long-term consequences.

The question of how and why innovations spread through populations has been the focus of extensive research in various scientific disciplines over recent decades. Generally, innovation diffusion is defined as the process whereby a few members of a social system initially adopt an innovation, then over time more individuals adopt until all (or most) members have adopted the new idea (e.g. Rogers 2003; Ryan and Gross 1943; Valente 1993). Anthropologists and archaeologists have argued that this process is one of the most important processes in cultural evolution (Richerson et al. 1996) and much work has been devoted to describing and analysing the temporal and spatial patterns of the spread of novel techniques and ideas from a particular source to their present distributions. Classic case studies include the spread of agricultural inventions such as hybrid corn (e.g. Griliches 1957; Ryan and Gross 1943), the spread of historic gravestone motifs in New England (Dethlefsen and Deetz 1966; Scholnick 2012), and the spread of bow and arrow technology (Bettinger and Eerkins 1999). (For a more comprehensive list see Rogers and Shoemaker (1971) who reviewed 1,500 studies of innovation diffusion.) Interestingly, the temporal diffusion dynamic in almost all case studies is characterized by an S-shaped diffusion curve describing the fraction of the population which has adopted the innovation at a certain point in time. Similarly, the spatial dynamics tend to resemble travelling wave-like patterns (see Steele 2009 for examples). The basic puzzle posed by innovation diffusion is the observed lag between an innovation’s first appearance and its general acceptance within a population (Young 2009). In other words, what are the individual-level mechanisms that give rise to the observed population-level pattern? Again, scientific fields as diverse as economics/marketing science (e.g. Bass 1969; Van den Bulte and Stremersch 2004; Young 2009), geography (e.g. Hägerstrand 1967), or social science (e.g. Henrich 2001; Steele 2009; Valente 1996; Watts 2002) offer interesting insights into this question without reaching a consensus about the general nature of individual adoption decisions. In archaeological and anthropological applications, population-level patterns inferred from the archaeological record, such as adoption curves, are often the only direct evidence about past cultural traditions (Shennan 2011).

Previous articleNext article No AccessNew Biological BooksBehavior Pattern and Process in Cultural Evolution. Origins of Human Behavior and Culture, Volume 2. Edited by StephenShennan. Berkeley (California): University of California Press. $60.00. vii 341 p.; ill.; index. 9780520255999. 2009.R.LeeLymanR.LeeLymanAnthropology, University of Missouri, Columbia, Missouri Search for more articles by this author Anthropology, University of Missouri, Columbia, MissouriPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by The Quarterly Review of Biology Volume 84, Number 3September 2009 Published in association with Stony Brook University Article DOIhttps://doi.org/10.1086/644687 Views: 6Total views on this site 2009 by The University of Chicago Press. All rights reserved.PDF download Crossref reports no articles citing this article.

Within the field of cultural evolution, particular attention has been devoted to the process of cumulative cultural evolution (CCE). Much of modern human behaviour is believed to be attributable to CCE. Despite common consensus over the importance of this topic, there are disparities in how the term has been defined and interpreted (and correspondingly the breadth of phenomena it is considered to encompass). Defined broadly, CCE refers to processes of cultural change involving alterations in cultural traits occurring over multiple episodes of social transmission, but there is variation in the additional criteria considered to be defining features. This chapter will highlight points of contention by examining some key borderline cases, which illustrate how the preferred definition of CCE impacts its presumed scope (e.g. whether it is restricted to humans). It is likely that differing motivations for interest in CCE underpin some of the differences in characterization of the process.

I propose a mathematical model of cultural evolution to explain why false theories and meaning systems or maladaptive beliefs may spread and become fixed in a population while assuming that their diffusion rates are lower than their true counterparts. By combining ideas from judgment aggregation and the Condorcet Jury theorem with cultural evolution dynamics, I introduce a new epistemic stage in the cultural evolution process where culturally transmitted theories not only spread “horizontally” (across individuals in the same generation) and “vertically” (from one generation to the next), but also inside individual brains (“personal reflection process”). This occurs when a brain adopts a maladaptive theory (not received from outside) by means of internal inference from other false premise/idea that was indeed received culturally. In this context, false theories may favor the assumption of other false theories after the individuals have been exposed to true information about their logical connection, and increase their presence in the population within the normal and adaptive logical working of our brains. Using a simple stylized model and subsequent simulations I identify the parametric conditions in which false theories become universally accepted, so that the model could be tested empirically.

Abstract: In this paper I argue, first, that human lifeways depend on cognitive capital that has typically been built over many generations. This process of gradual accumulation produces an adaptive fit between human agents and their environments; an adaptive fit that is the result of hidden‐hand, evolutionary mechanisms. To explain distinctive features of human life, we need to understand how cultures evolve. Second, I distinguish a range of different evolutionary models of culture. Third, I argue that none of meme‐based models, dual inheritance models, nor Boyd and Richerson's models fully succeed in explaining this adaptive fit between agent and the world. I then briefly develop an alternative. Finally, I explore (in a preliminary way) constraints on cultural adaptation. The processes of cultural evolution sometimes built a fit between agents and their environment, but they do not always do so. Why is folk medicine, for example, so much less reliable than folk natural history?

Domestic spaces as crucibles of Paleolithic culture: An archaeological perspective

Niche construction is an endogenous causal process in evolution, reciprocal to the causal process of natural selection. It works by adding ecological inheritance, comprising the inheritance of natural selection pressures previously modified by niche construction, to genetic inheritance in evolution. Human niche construction modifies selection pressures in environments in ways that affect both human evolution, and the evolution of other species. Human ecological inheritance is exceptionally potent because it includes the social transmission and inheritance of cultural knowledge, and material culture. Human genetic inheritance in combination with human cultural inheritance thus provides a basis for gene-culture coevolution, and multivariate dynamics in cultural evolution. Niche construction theory potentially integrates the biological and social aspects of the human sciences. We elaborate on these processes, and provide brief introductions to each of the papers published in this theme issue.

This study provides an account of how a naturalistic orientation in epistemology known as evolutionary epistemology can benefit from integration with some more recent advancements in cultural evolutionary theory. In particular, this thesis explores the ways in which a Darwinian selective framework of culture provides new insights to rethink unsolved epistemological disputes and problems such as the growth of scientific ideas, the notion of scientific progress, the ‘context distinction’, the theory ladenness of science and a demarcation criterion between science and other cultural realms. All these issues are approached from an evolutionary and selective standpoint that assumes that biological and cultural selection are representative of a wider and more encompassing selective process. Thus, the thesis also explores theoretical disputes concerning the analogies and disanalogies between cultural and biological selection. Five early evolutionary analogies of knowledge accretion are explored in the first chapter setting the context of the debate for the epistemological issues that are connected in the other chapters to cultural evolution. Here, a populationist account of scientific ideas is presented as a viable model to study the conceptual and ‘ideational’ dynamics of change in science. In the last part of this work, my populationist and selective model is applied to study a specific scientific innovation: a molecular technique for taxonomic identification and classification known as DNA barcoding. Finally, the last chapter explores the use of text analysis to investigate the network of concepts and ideas that relate to the ‘DNA barcoding’ concept’. Here, I evaluate the impact of this technique on the fields of taxonomy/systematics, particularly, for what concerns the so called ‘species problem’.

Balancing evidence and norms in cultural evolution

The interest in theoretical frameworks that improve our understanding of social-ecological systems is growing within the field of ethnobiology. Several evolutionary questions may underlie the relationships between people and the natural resources that are investigated in this field. A new branch of research, known as evolutionary ethnobiology (EE), focuses on these questions and has recently been formally conceptualized. The field of cultural evolution (CE) has significantly contributed to the development of this new field, and it has introduced the Darwinian concepts of variation, competition, and heredity to studies that focus on the dynamics of local knowledge. In this article, we introduce CE as an important theoretical framework for evolutionary ethnobiological research. We present the basic concepts and assumptions of CE, along with the adjustments that are necessary for its application in EE. We discuss different ethnobiological studies in the context of this new framework and the new opportunities for research that exist in this area. We also propose a dialog that includes our findings in the context of cultural evolution.

Recent Publications on Archaeological Ceramic Analyses and their Contributions to the Study of Ancient Pottery Technology

Grouping behavior has various types of antipredator functions. Some of these functions require social transmission of information, such as the many-eyes effect, whereas others do not, such as the dilution and confusion effects. Functions of grouping behavior would enhance with social transmission among group members. We investigated and compared the onsets of schooling behavior and social transmission of information in chub mackerel Scomber japonicus. Onset of schooling behavior was observed in rearing tanks by calculating the degree of parallel swimming. Onset of social transmission was examined by using visual cues from conspecifics. A group of five individuals was put in each of three experimental chambers from which they could see a group of conspecifics in the neighboring chamber. A weak electric stimulus was given to one of these chambers, and information transfer among individuals was observed. We found that social transmission by visual cues started on 30 days posthatching (25.1 mm in standard length), which was 2 weeks after the onset of schooling behavior. The late onset of social transmission relative to schooling behavior might be attributed to different predation pressure with development, or by underdevelopment of optic tectum, as the volume of the optic tectum did not increase just after the onset of schooling behavior.