CHAPTER 3: THEORY: TOWARD A UNIFIED EVOLUTIONARY APPROACH
One of the most significant challenges facing the application of evolutionary theory to the corrugation problem, or any other specific problem in the social sciences, comes from the wide range of opinion regarding the appropriate features of a viable evolutionary approach (e.g., Barton and Clark 1997; Boone and Smith 1998; Dunnell 1980, 1989; Durham 1991; Flinn 1997; Hallpike 1988; Lyman and O'Brien 1998; Maschner 1996a; Rindos 1985; Rosenberg 1994; Spencer 1997; Sperber 1996; Trigger 1998 ). Several schools of evolutionary thought have developed within the social sciences including sociocultural evolutionism, cultural selectionism, cultural transmissionism, coevolutionism, processualism, evolutionary archaeology, human evolutionary ecology, sociobiology, evolutionary psychology, cultural virus theory, and memetics. Although some of the differences among these evolutionary approaches are substantial, many points of disagreement are very subtle and difficult to follow.
Rather than try to characterize and sort out each of these approaches, I think much of the discord among evolutionists can be captured with a simpler classification based on the extent to which cultural change is seen to conform to the Darwinian processes. Three different idealized positions can be identified. On the pro-Darwinian side, cultural change is thought to have all of the features necessary (variation, replication, and sorting) to qualify as a fully Darwinian process. This position follows from the argument that human communication and social learning create a Darwinian process operating parallel to, and, to a variable extent, separate from biological evolution ( Boyd and Richerson 1985; Brodie 1996; Campbell 1965, 1977, 1988; Cavalli-Sforza and Feldman 1981; Cloak 1975; Dawkins 1976, 1982; Dennett 1995; Dunnell 1978b; 1980; 1989; Durham 1991; Goodenough 1995; Hull 1982, 1988b; Leonard and Jones 1987; Lynch 1996, 1998; O'Brien 1996b; Rindos 1984, 1985, 1986, 1988; Teltser 1995). Another position takes the overall directionality and apparent progress of cultural change and unique aspects of human cognition and culture as evidence that Darwinism is a failed analogy for cultural evolution. Instead, proponents of the non-Darwinian evolutionary position argue that systemic relationships within societies and purposeful actions by individuals create unique mechanisms of cultural change that make it more analogous to the growth and development of organisms than to natural selection ( Blanton et al. 1996; Brumfiel 1992; Carneiro 1972, 1992; Demarest 1989; Earl and Preucel 1987; Flannery 1972; Hallpike 1988; Harris 1977, 1979; Johnson and Earl 1987; Kosse 1994; Marcus and Flannery 1996; Rosenberg 1994; Spencer 1997; Trigger 1998; Wright 1984). Between these two positions lies the third view that rejects the notion that cultural change per se is Darwinian because of a lack of viable cultural replicators. Proponents of this position argue that cultural change is made possible and directed by evolved constraints and plasticity in human decision making. From this perspective, cultural evolution is seen as the cumulative, and usually adaptive, effect of the human ability to flexibly apply evolved decision rules to cope with problems presented by changing social and ecological conditions ( Barkow et al. 1992; Boone and Smith 1998; Flinn 1997; Hawkes and O'Connell 1992; Hawkes et al. 1997; Hill and Hurtado 1995; Mithen 1990; 1997; Pinker 1997; Smith 1991, 1992; Smith and Winterhalder 1992; Sperber 1996; Winterhalder and Goland 1993; Winterhalder and Smith 1981).
To evaluate these different positions adequately, it is important to be very clear and explicit about what we mean by the Darwinian process. Perhaps no single problem has resulted in greater confusion and conflict than subtle differences in meaning people bring to discussions of Darwinian evolution. Many of these differences in meaning can be traced back to how much and what aspects of the biological heritage of Darwinism have been retained in its application to cultural variation and change. However, the Darwinian process is not strictly biological, but is a general algorithmic process that can improve the fit between particular kinds of entities and their environment ( Campbell 1974; Dennett 1995; Lewontin 1970). Consequently, the first section of this chapter is devoted to presenting an abstract, non-biological view of the essential features and units of the Darwinian process. In the process, I introduce a notion of frames of reference, which becomes a central theme in considering evolutionary explanations of cultural change. Next, I address several objections raised against the broad applicability of the Darwinian process to cultural change. These objections include the reality of cultural replicators, the role of human behavioral plasticity, the importance of human intention and decision making, and the possibility of directed, orthogenic change in large-scale sociocultural systems. In each case, arguments have been made that features of human cognition, behavior, or social systems eliminate the Darwinian process as a viable model of cultural change. In evaluating these arguments, I find that some arise from the intrusion of common sense, while others stem from the adoption of one frame of reference to the exclusion of all others. However, none of these objections successfully undermines the applicability of the Darwinian process to cultural evolution. In fact, by recognizing the potential for multiple, causally relevant frames of reference, we see the importance of the Darwinian process to understanding cultural change.
The Darwinian Process
Recent interest in expanding the explanatory reach of evolutionary theory, together with a controversy over the units of selection in biology, have led to several attempts to identify the fundamental features of the Darwinian process, and generalize Darwinian ideas beyond those features relevant only to biological evolution ( Brandon 1982, 1990; Brandon and Burian 1984; Calvin 1996a, 1996b, 1997; Campbell 1974; Dawkins 1976, 1978, 1982; Dennett 1995; Eldredge 1985; Ghiselin 1997; Gould 1982, 1989; Heyes and Plotkin 1989; Hull 1980, 1982, 1987, 1988a, 1988b; Lewontin 1970, 1982; Lloyd 1992; Lipo and Madsen 1998; Pocklington and Best 1997; Rose 1998; Salthe 1985; Sober 1984; Sober and Wilson 1994; Vrba and Eldredge 1984; Vrba and Gould 1986; Wilkins 1998; G. C. Williams 1966; M. B. Williams 1989). Many aspects of this literature have influenced my understanding of the conceptual structure of Darwinism, but my views conform most closely to those of David Hull, a philosopher of biology who has used Darwinian theory to explain variation and change in scientific concepts. I employ several of his terms and concepts in the following discussion. I should also point out that I use the term "Darwinian Process" in deference and recognition of Darwin's brilliant, seminal insights, and not because the ideas I present are based strictly on his. We have learned a great deal in the 140 years since Darwin radically altered our view of life, and I try to take full advantage of that knowledge. I could adopt the term neo-Darwinian, but that has already been applied to a very narrow view of biological evolution, and one of my goals is to distance the theory from biology. Rather than invent another neologism, I have decided to stay with "Darwinian."
Essential Features
In its most abstract form, the Darwinian process is the differential copying of heritable variation. This process has three essential featuresÑreplication, variation, and sorting. Replication requires a means for making copies of a given pattern or structure. The physical entities exemplifying a particular pattern are referred to as replicators. Variation consists of the creation or introduction of variant states, or traits in replicators. Sorting involves the filtering of the variant replicators resulting in biased or differential replication. Thus, each of these parts of the Darwinian process entails the operation of one or more mechanisms on classes of entities that are defined in terms of their role in the process itself. To make this clearer, let's take a closer look at each of these features.
Genes are archetypal replicators. During meiosis and mitosis, DNA strands within cell nuclei unravel and the bonds between base pairs are broken yielding two halves, which form the basis for reconstituting two separate DNA strands. These DNA replicas, together with certain enzymes and membrane tissues, split apart to form new cells. This specific and well-documented mechanism of replication has tended to bias our view of replication generally as being self-starting, particulate and involving the movement or transmission of a material pattern from parent(s) to offspring. However, nothing in the nature of the Darwinian process requires that all replication match that found in DNA. All that is required is the copying of some pattern such that offspring resemble their parent or parents more than they do non-parents ( Calvin 1997; Hull 1980, 1988b). The particular material constituting the pattern need not be copied or transmitted. It is the replication of the pattern that is important because of the pattern's potential to contain, or code for information. This pattern copying definition of replication creates room for a wide variety of replicators (specific entities being copied) and mechanisms (particular copying procedures) of replication, of which self-replication is only one example ( Ghiselin 1987, 1997; Vaneechoutte 1998). Although theoretical and philosophical considerations of the nature and relative importance of different replicates are useful, ultimately, identifying and documenting the replicators and replication mechanisms involved in any particular case is an empirical problem ( Pocklington and Best 1997).
If replication transpires with 100% fidelity, there can be no Darwinian evolution. The Darwinian process requires some variation through which various sorting mechanisms can work to produce differential replicative success. On the other hand, the replication process must occur with some degree of fidelity, or there is no inheritance. Without inheritance, change can still occur, but it would be completely random and chaotic with no potential for directionality or improvement. Although very high fidelity in replication is an important part of the operation of some sorting mechanisms, such as directional selection, it is not an essential feature of the general Darwinian process. The amount of variation between parent(s) and offspring must be low enough to avoid error catastrophe, the inability to maintain adaptive functional integration in the face of high mutation rates ( Eigen and Schuster 1979; Kauffman 1993, 1995; SolŽ et al. 1999), and yet be less than 100% faithful.
In biology and elsewhere (e.g., Rindos 1989), it is also commonly argued that the generation of variation must be random with respect to fitness. In other words, the environment cannot instruct or determine the kind of new variation produced. This aspect of Lamarckism has been rejected by biologists because of the well-documented one way flow of information from the replicators in the germ line to those in the soma or body, known as the Weismannian barrier and forming the central dogma of molecular biology ( Dawkins 1986; Ridley 1985; Weismann 1893). However, this too is not an essential feature of variation in the Darwinian process. Directed variation does not preclude Darwinian evolution. In fact, recent advances in our understanding of self-organization indicate how the emergence of new variants can, even in biology, be ordered and directed in particular ways ( Holland 1995, 1998; Kauffman 1993, 1995). As long as heritable variation exists among replicators, however that variation is produced, the full Darwinian process can occur. Issues involving both copying fidelity and directed variation have led some to reject cultural change as Darwinian. Consequently, I revisit to these topics in more detail later in this chapter.
The final part of the Darwinian process is sorting. As noted above, sorting involves the differential copying of variant replicators such that the frequencies of replicator traits change across replication events, or generations. Sorting takes place through two general mechanisms - selection and drift. Selection occurs when competition, created by environmental limits, exits among variable replicators, and the interaction of replicators with the environment, including each other, causes differential replicative success ( Hull 1980, 1988b; Vrba 1984; Vrba and Gould 1986). Hence, there is a correlation between certain variants, or variant suites, and replication success that is determined, or caused by the nature of interaction. It is the relationship between interaction and replicative success that defines the fitness of variant traits. Over multiple generations (defined by replication events), selection tends to improve the fit, or adaptiveness of replicating and interacting entities to their environment by altering the frequency of replicator and interactor traits in larger scale aggregates, populations and lineages.
In contrast to the deterministic effects of selection, drift, the second general sorting mechanism, involves stochastic effects of random sampling errors that occur during replication ( Beatty 1992; Wright 1931, 1932, 1949). Although drift works without regard to fitness differences, it is most prevalent as a sorting mechanism when alternative traits are selectively neutral. Selective neutrality can arise by either traits being equally fit or traits have very little or no impact on fitness because they are not involved in any interaction ( Hull 1988b; Kimura 1983, 1992; King and Jukes 1969). The size of the replicator transmitting population also impacts the likelihood for drift to sort traits, even those with potentially adaptive consequences. In very large populations, the effects of drift tend to be negligible. That is, no significant change occurs in trait frequencies from one "generation" to the next (Boyd and Richerson 1985). However, in small populations, drift leads to the fixation of traits (one trait survives while others are lost) and the homogenization of populations. The smaller the population, the more rapid the rate of fixation ( Cavalli-Sforza and Feldman 1981; Neiman 1995). Mechanisms that introduce new variation, such as mutation, innovation and migration, counteract the tendency for drift to produce homogeneous populations ( Neiman 1995). Thus, for selectively neutral or weakly selected (those having small fitness values) traits, drift can result in fixation with the rate dependent on the population size, mode of replication (mainly generation length), and the rate at which new traits are introduced.
The operation of all three features of the Darwinian process, replication, variation, and sorting, results in descent with modification, or Darwinian evolution. Loss of any one of these features renders the Darwinian process inoperative. For example, selective sorting of variant entities occurs frequently in nature, such as the separation of sediment by grain size during erosion or deposition. However, in the absence of viable replication, this sediment sorting process is non-Darwinian. An astute critic might argue that the break down of sediment into smaller particles is a form of replication, but, in this case, replication of the relevant pattern, namely grain-size, has not occurred.
It is also possible and, indeed, common to add features to the Darwinian process that can catalyze, constrain, or inhibit the process. This is usually done when considering specific problems, cases, or entities. Biologists have built a tremendous body of knowledge of particular mechanisms and conditions that play important roles in biological evolution. Although understanding these features is essential for generating explanations of specific cases of biological evolution, they do not necessarily constitute essential features of other forms of Darwinian evolution. Consequently, we must be very careful when using the literature on biological evolution to draw insights regarding the applicability of the Darwinian process to cultural change.
Units
Before turning to a consideration of whether cultural change is Darwinian, we need to focus more explicitly on units. Failure to adequately address and clarify unit issues has been a major source of confusion and friction in studies of cultural and biological evolution ( Dunnell 1986b, 1995; Ghiselin 1989, 1997; Hull 1980, 1988a, 1988b; Lipo and Madsen 1998). Specifically, confusion concerning two unit issues has been especially damaging. These are the distinction between conceptual and empirical units, and relationships among units at different scales. Consequently, I will focus on these two more philosophical unit issues here, but addressing other issues involving the validity and reliability of units will be a recurring theme throughout this dissertation.
As I discussed in Chapter 1, conceptual units (also termed theoretical units, classes, and universals) and empirical units (also termed individuals and particulars) occupy very different roles in scientific explanation. Conceptual units have the following characteristics: they are abstract, they have defining properties, they have instances, they are spatially and temporally unrestricted, and when organized hierarchically, they are related by inclusion. Empirical units, on the other hand, are concrete, have no defining properties or essences, have no instances, are spatially and temporally restricted, and when organized hierarchically, are related by part-whole incorporation rather than inclusion (see Ghiselin 1997 for an extended discussion of this distinction and its importance in biology). Because they are concrete, empirical units can also participate in processes whereas conceptual units cannot because they are abstract and unrestricted. However, conceptual units, when formulated properly by intentional definition, are the entities referred to by laws of nature, and thus, serve to define the processes in which empirical units can participate. In other words, universal laws must be generalizations about conceptual units, not empirical units that are spatially and temporally restricted. When these conceptual units are embodied by measurable empirical units, it becomes possible to explain the regularities, variation, and change of particular entities in terms of universal laws. Much of the controversy over the existence of laws of history stems from neglecting the distinction between conceptual and empirical units ( Dunnell 1982; Ghiselin 1997; Mayr 1982; Popper 1964; Smart 1963).
In the previous discussion of the essential features of the Darwinian process, five different units, traits, replicators, interactors, environment, and evolvers (populations or lineages) were mentioned. All of these are conceptual units. They identify the kinds of entities required for and resulting from the operation of the Darwinian process, and each is defined in terms of the process itself. These five units can also be arranged hierarchically (Figure 3). Traits, which make up the lowest level of the hierarchy, are properties of replicators, interactors, and the environment that can vary, and thus have an impact on differential replicative success. Replicators, interactors and the environment occupy the middle level of the hierarchy. Replicators are patterned entities that are copied reliably over successive generations ( Hull 1980, 1988b:408). Interactors are entities that interact with the environment as a cohesive whole in such a way as to bias replication ( Hull 1980, 1988b:408). The environment consists of those external entities that interactors interact with ( Brandon 1990). Evolvers, the upper-most level of the hierarchy, are entities that are related by descent, and are cohesive with respect to particular sorting mechanisms or forces ( Hull 1980, 1988b:409; M. B. Williams 1989). Evolvers, as the units of evolution, also provide the relevant counting frame from which to document changing frequencies of other units ( Lipo and Madsen 1998).
Figure 3. Hierarchical relationships among conceptual units in evolutionary theory.
All of these units are defined in terms of their relationships to one another in the Darwinian process. These dialectical relationships also make it difficult, and, in some cases, impossible to identify particular instances of one unit without reference to another ( Levins and Lewontin 1985; Lewontin 1982). For example, interactor and environment are defined in relation to each other, and how that relationship affects replication success. Thus, there is no interactor independent of the environment, and no environment without an interactor, and the interactor-environment relationship specifies the domain of relevant replicators. The replicator-interactor-environment relationships also determine the kinds of information, defined as differences that make a difference ( Bateson 1972, 1979), that are relevant to evolution. So, in addition to identifying material (matter and energy) relationships, these conceptual units also specify relationships of meaning, a kind of evolutionary semiotics ( Emmeche and Hoffmeyer 1991; Hoffmeyer 1996, 1997; Hoffmeyer and Emmeche 1991).
Remaining cognizant of the distinction between conceptual and empirical units becomes critical when we shift focus from these conceptual units to the empirical entities that instantiate them. There is no necessary, fixed, or predetermined relationship between conceptual units and the particular empirical units to which conceptual units refer. Different conceptual units may simultaneously refer to the same empirical entity, and multiple, different empirical units can be instances of the same conceptual unit. For example, although replicators and interactors define different roles in the Darwinian process, the same physical entity may function in both roles. In biology, individual organisms can be both replicators and interactors. In addition, empirical entities can also have different roles in the Darwinian process, exemplify different conceptual units, depending on the scale of the particular frame of reference. In other words, the inclusive hierarchy of conceptual units can slide up or down different scales of a part-whole hierarchy of empirical units. This flexible relationship between conceptual and empirical units means that the Darwinian process can be operating simultaneously across multiple empirical units and scales. Consequently, we must rely on the nature of the particular research problem to specify the relevant or appropriate reference scale(s) and unit identifications (Kawata 1987). This notion of the relativity of frames of reference, or the variable relationship between conceptual and empirical units, has major implications for how we conceive of cultural change in evolutionary terms.
Is Cultural Change Darwinian?
Working from this understanding of the Darwinian process, we can now evaluate the different objections and reservations raised to applying Darwinian theory directly to cases of cultural change. Four issues occur again and again in discussions both critical and supportive of viewing cultural change as a Darwinian process. Three of these issues focus on different parts of the Darwinian process (replication, variation, and sorting), and question whether each is present in cultural change in a form sufficient for Darwinian evolution to occur. The fourth issue involves a question of the appropriate scale for explanation of cultural change, and whether the Darwinian process is the most important process of change at that scale. We can now examine each of these issues in light of the previous discussion of the Darwinian process.
Cultural Replication
As we have seen, replication, the copying of some pattern with a specifiable degree of fidelity, is an essential feature of the Darwinian process. Social learning among humans has long been thought to be analogous, in some ways, to the biological transmission of information through the replication of genetic material. Over the last 20 years, this notion has been developed into a full-fledged theory of cultural inheritance involving the transmission, or replication, of ideas, behaviors, and material traits by imitation and other forms of social learning (e.g., Alexander 1979; Ball 1984; Boyd and Richerson 1985; Cavalli-Sforza and Feldman 1981; Cloak 1975, 1986; Cullen 1996; Dawkins 1976, 1982; Dennett 1995; Durham 1991; Goodenough 1995; Hull 1982; Lumsden and Wilson 1981; Pulliam and Dunford 1980; Rindos 1985). From this perspective, human behavioral variation and change are, in part, a consequence of a dual inheritance, genetic and cultural, with varying opinions on the degree of autonomy between these different inheritance systems.
Recently, the term "meme" has been used to denote a unit of cultural replication. The biologist Richard Dawkins coined the term meme in his book The Selfish Gene, and defined a meme as "a unit of cultural transmission, or a unit of imitation" (1976:206). As examples of memes, he identified "tunes, ideas, catch-phrases, clothes fashions, ways of making pots or of building arches" (1976:206). Dawkins conceived of memes as analogous to genes, which he sees as the fundamental unit of biological replication. Subsequently, Dawkins restricted his notion of meme to "a unit of information residing in a brain" (1982:109) to distinguish between the meme as replicator and meme products, behaviors and artifacts, which he came to see as phenotypic effects and not replicators. This notion of cultural replicators as mentally stored information, in short, beliefs and ideas, has come to dominate most considerations of cultural replication (e.g., Boyd and Richerson 1985; Brodie 1996; Dennett 1995; Durham 1991; Laland 1992; Lynch 1996, 1998; Takahashi 1998). I think this is an unnecessarily restrictive view of cultural replication, just as Dawkins's "selfish gene" view of biological replication is instructive yet overly restrictive. However, before presenting my views on the nature of cultural replication, we need to consider the possibility that the whole notion of cultural replication is misguided.
The idea that cultural replication plays a crucial role in cultural evolution has been strongly criticized, and, thus, should not be taken for granted. Two different kinds of critiques exist. One disputes the reality of cultural replication, while the other questions its fidelity, and thus its ability to function in a fully Darwinian process of cultural change ( Cziko 1995:176-178; Flinn 1997; Flinn and Alexander 1982; Harms 1996; Mithen 1997; Pinker 1997:208-210; Sperber 1996:100-106). Both criticisms derive from problems engendered by the strictly ideational view of cultural replication as analogous to genetic replication. The basic problem is that, in the absence of telepathy, there is no mechanism for replicating the ideas and beliefs in one person's mind to the mind of another. In addition, the brain does not store ideas and beliefs as discrete neurological entities that are the same in all individuals ( Gazzaniga 1989, 1992). Consequently, neurological structures or patterns corresponding to specific ideas, beliefs, or behaviors cannot be copied directly from one individual to another. Instead, ideas and beliefs must be translated into behaviors, or other phenotypic expressions for communication and transmission to occur.
If ideas and beliefs, the only cultural replicators in the ideational view, cannot be copied directly from one person to another, then these mental representations must be constructed anew by each individual through observation and contemplation of their environment, including the phenotypic expressions of other individuals. Not only does this undermine the simplistic ideational view of cultural replication, but it also forms the basis of the view that cultural transmission (communication and social learning) lacks sufficient fidelity to support a fully Darwinian process of cultural change. The notion here is that the individual construction of knowledge entailed in cultural transmission involves so many cognitive and physiological filters that it is more appropriately thought of as a process of transformation than replication ( Sperber 1996). Specific details, the texts if you will, are often lost or garbled in this process whereas more general themes that resonate with particular filters are preserved ( Heyes and Plotkin 1989). Thus, it is the nature of the filters involved in communication and the formation of mental representations that forms the causal basis of cultural change, leaving only a marginal role for the accurate replication of ideas.
Dennett (1995:352-360) has responded to these criticisms by arguing that memes are semantic, rather than syntactic, replicators. In other words, it is information, or meaning that is transmitted in cultural replication, not particular neurological or linguistic patterns. The tight correspondence between syntax and meaning present in genetic replication is just not a central feature of cultural replication. Instead, cultural replication is more analogous to transmission of radio or television signals where a pattern of information is maintained across multiple codes (digital and analog) and substrates (electromagnetic waves, conducted electrons, vibrating membranes, electro-chemical impulses, etc.). Dennett recognizes the importance of the filters involved in sorting among variant memes, but he also sees an understanding of the replication of particular kinds of cultural information as equally important for scientific explanation of cultural change. Although Dennett's approach may suggest a way to salvage the ideational view of cultural replication, it also carries with it some formidable epistemological challenges.
For the same reason that it is impossible for mental representations to be transmitted from mind to mind, it is impossible to know, through measurement, the contents of other people's minds ( Gatherer 1998). As I discussed briefly in Chapter 1, we are particularly adept at making inferences about the contents of other people's minds based on observations of their behavior (including linguistic communication), and introspection regarding our own thoughts. However, these inferences are notoriously unreliable. Although this is often seen as a methodological problem that may be overcome with advances in brain imaging technology, I suspect that there is a deeper problem here. It is likely that no simple one-to- one relationship exists between particular mental representations and consequent actions. Thus, using actions and artifacts to gauge accurately the content of hidden mental representations becomes a truly daunting task. The reverse is also true. Even if we were able to measure somehow the state of mental representations in someone's brain, this would not necessarily give us the power to predict accurately all actions. This is the situation found in biology where complex relationships among different parts of the genome, and between the genome and the environment result in a highly variable and often probabilistic relationship between genotypes and phenotypes.
Do these theoretical and methodological problems so undermine the notion of cultural replication that it negates the possibility that the Darwinian process is an accurate model of cultural change? Both sets of problems stem from relying exclusively on the ideational notion of cultural replicators. There is nothing in the Darwinian theory of replication that would limit cultural replicators to mental representations. The ideational replicator notion comes from an inappropriate borrowing of the genotype-phenotype distinction from biology. In the discussion of the Darwinian process, I did not include the genotype-phenotype distinction as an essential feature. Instead, I made a conceptual distinction between replication and interaction. The particular empirical entities that function in these necessary evolutionary roles can correspond to genes (genotype) and organisms (phenotype) as they often do in biology, but this is by no means a necessary condition. In fact, the same empirical entity can function in both roles, as was almost certainly the case in biology at the beginning of life ( Kauffman 1993:329-333).
All that is needed for Darwinian replication is the copying of a pattern with sufficient, though not always perfect fidelity. In addition to possible semantic replicators, several cultural entities can meet this definition of replication including behaviors, artifacts, factions, institutions, and societies to name only a few. These additional cultural replicators have the added advantage of being eminently measurable, thus avoiding the epistemological problems posed by semantic replicators. However, critics of these kinds of non-genetic and non-ideational replicators emphasize their lack of ability to self-replicate ( Leonard and Jones 1987; Lyman and O'Brien 1998). Behaviors, artifacts, and larger scale cultural entities ultimately require people for replication, and cannot make copies of themselves indefinitely as some biological replicators may be able to do. However, self-replication is not a defining feature of a Darwinian replicator. Few, if any, would question the identification of DNA as a viable Darwinian replicator. Nonetheless, DNA replication requires the assistance of a suite of enzymes called DNA polymerases. DNA molecules are reproductively inert in the absence of these enzymes. Cells may be the only truly self-replicating entities, and even this is open to debate, as cells require food to maintain the machinery of replication. Thus, limiting replicators to those that can self-replicate is not only unnecessarily restrictive, but it would eliminate many entities that are currently considered viable Darwinian replicators.
The fact that behaviors, artifacts, and other non-ideational cultural entities can be interactors and even features of the environment should not be confused with their ability to function in replication as well. As discussed earlier, the evolutionary function of any given entity depends primarily on the particular frame of reference one adopts. From the perspective of people as biological organisms, behaviors and artifacts are indeed part of the phenotype of the organism (functioning as an interactor) when they are one's own, and part of the environment when they belong to others. Nevertheless, there is little, and possibly no valid a priori justification for privileging this or any other particular frame of reference over others, such as the perspectives of the behaviors and artifacts themselves. As we shift the frame of reference, the functions performed by various entities may also shift.
Given the current influence of the ideational notion of cultural replication, and the long tradition in archaeology of discounting artifacts and behaviors as viable Darwinian replicators (e.g., Brew 1946; Leonard and Jones 1987; Lyman and O'Brien 1998), I should elaborate more thoroughly on my rather unorthodox view on non-ideational replicators. Let us begin with behavior. One can question whether behavior is a true replicator by arguing that behaviors can not be copied independently of the ideas or mental representations that generate them. There is no doubt that all human behaviors involve some form of activity by the nervous system, and often considerable cognitive processing is required to match behaviors appropriately to different stimuli. In addition, the basic neurological configurations that process stimuli and produce behaviors are quite similar from one individual to another. Consequently, behaviors copied by one person from another involve activation of many of the same nervous system components. However, these neurological commonalties do not entail that the symbolic mental representations (beliefs, ideas, etc.) that might motivate the similar behaviors are also the same. In other words, behaviors can be imitated without any transmission or copying of the conscious or unconscious mental states involved. For example, I can watch a person make a pot on a video with the volume turned all the way down, and copy that person's behavior without any knowledge of her motivations, beliefs, or ideas concerning why and how she is making the pot that way. Young children copy all manner of behaviors, for better or worse, well before they are linguistically, and likely, cognitively capable of understanding the motivations. It is even easier, quite often, to show adults how to do something than to describe it to them, although a combination of description and action probably results in the highest copying fidelity. Differences in copying fidelity notwithstanding, it should be clear the behaviors can be copied independently of ideas, and it is a matter for empirical research to determine if this kind of replication has occurred in a given situation.
A similar question of copying independence can be asked of artifacts. In this case, one wonders whether artifacts can be copied independently of the behaviors required in producing them. Certainly, the easiest way to learn how to make something is to watch and listen to someone while they are making it, and then try it yourself with their supervision. However, it is also possible to copy an artifact by only examining the artifact itself, and never actually seeing the behaviors or hearing the ideas of anyone else making the artifact. Given the limits on what is physically possible, particularly with things made by hand, it is likely that many behaviors will be employed in copying an artifact that are very similar, if not identical, to those unobserved behaviors used to make the original. However, these behavioral similarities can not be considered replicates because they arose through constraints rather than copying. Copying of artifacts and attributes of artifacts without observation of the behaviors involved in making them is a common practice among archaeologists. We frequently copy ancient artifacts that are no longer made today and thus, production behaviors cannot be observed. In addition, we often employ techniques and technologies that could not have been used by the ancient artisans. Despite limits to our knowledge of ancient behaviors, and known behavioral deviations, it can be extremely difficult to distinguish the copy of an artifact from the original. Indeed, as discussed in the next Chapter and in Chapter 7, I employed just such an artifact replication procedure as part of the experimental research conducted for this study.
That the replication of cultural entities, including ideas, behaviors, artifacts, and more, requires other entities, here biological organisms, capable of social learning and imitation should not discourage us from recognizing these entities as viable Darwinian replicators. Once we appreciate that self-replication is not essential to the definition of a Darwinian replicator, a world of possibilities opens up. Although it may be possible to explain many aspects of cultural variation and change from the perspective of biological replicators, this is an empirical claim subject to evaluation, not a theoretical or philosophical principle. Other frames of reference may be equally, or perhaps more, valid for explaining particular aspects of cultural change than that derived exclusively from biology. This frame of reference problem is not restricted only to culture. The same issues occur in biology, and manifest themselves most explicitly in the context of the levels of selection controversy. Identifying the most appropriate frame or frames of reference for a given problem constitutes one of the principal challenges in constructing evolutionary explanations.
Behavioral Plasticity
Most organisms posses some ability to modify their behavior, physiology, or morphology in response to changing environmental conditions. Biologists call this ability phenotypic plasticity, and a large and complex literature exists on the topic ( Gordon 1992). Many anthropologists, particularly those strongly influenced by ecology, maintain that most examples of cultural change entail behavioral plasticity rather than the direct working of the Darwinian process (e.g., Boone and Smith 1998; Flinn 1997). This argument involves several issues including the nature of replicators, addressed in the previous section and the roles of directed problem solving, decision making, and human intentions in cultural change.
The basic argument for plasticity rather than Darwinian evolution turns on two points. First, most cultural change occurs quite rapidly in comparison to biological evolution through changes in gene frequencies. Consequently, it seems very unlikely that the impact of cultural changes on biological reproductive success could be the direct cause of changes in the frequencies of behaviors through time. Second, cognitive abilities, which are a direct consequence of Darwinian evolution, allow humans to make strategic responses to a variety of situations in which they find themselves. These strategic responses can include innovation or invention of novel behaviors and technologies as well as rational calculation and other forms of decision making among existing alternatives. The ability to direct variation and make decisions gives tremendous flexibility to human behavior. The evolved nature of these cognitive abilities also results in novel behaviors and decisions being adaptive for the organism, or its genes, more often than not. Because behavioral plasticity yields adaptive responses, it produces similar outcomes to evolution, but over much shorter periods.
Because proponents of this position often do not accept behaviors, artifacts, and, in some cases, ideas as viable replicators, they adopt a strictly biological frame of reference. Biological entities, mainly genes, but occasionally organisms and groups ( Sober and Wilson 1998; D. S. Wilson 1998; Wilson and Sober 1994), are the only true replicators. Consequently, behaviors and artifacts can only be part of the phenotype, that is, they can only function as interactors, not replicators. This conclusion is true only if we hold to a strict biological frame of reference. If we adopt a more flexible approach to frames of reference that allows cultural entities such as behaviors, artifacts, and ideas to function as replicators and other roles in the Darwinian process, the apparent distinction between behavioral plasticity and Darwinian evolution begins to break down.
Recognizing the existence of cultural replicators allows one to shift the frame of reference such that the decision rules and other cognitive, morphological, and physiological features of organisms, which facilitate their behavioral plasticity, now become features of the adaptive environment of these alternative replicators. This is a straight forward, logical deduction if one accepts the notion of cultural replication. It also forms the basis for a Darwinian concept of cultural selection in which cultural replicators compete in a complex environment composed of human cognition, social interaction, and physical possibilities (e.g., Braun 1995; Carneiro 1970; Campbell 1974; Cavalli-Sforza and Feldman 1981; Durham 1991; Fog 1999; Hill 1985; Pulliam and Dunford 1980; Rindos 1986).
Boone and Smith (1998:S168) have criticized this expanded view of Darwinian evolution calling it a semantic game that obscures important differences between biological and cultural change. Instead, they suggest that maintaining a biological frame of reference and seeing cultural change as involving unique mechanisms is preferable to adopting the perspective of the cultural replicators making a fully Darwinian account of cultural change possible. However, I can find no reason to be so restrictive, and see many potential benefits of embracing a more flexible perspective. For example, from a biological replicator frame of reference, cultural replication or transmission, as it is commonly referred to, looks extremely complex involving various unique biasing mechanisms (e.g., direct and indirect) and directions (vertical, oblique, and horizontal) with respect to biological generations ( Boyd and Richerson 1985; Cavalli-Sforza and Feldman 1981). By shifting to the frame of reference of the cultural replicators, these unique complexities of cultural change vanish. The biases are no longer seen as unique parts of cultural replication, but instead make up only a few of the many potential biasing mechanisms involved in Darwinian sorting. In addition, the complex relationship between cultural and biological transmission is simplified, as all cultural replication is vertical, one transmission event follows another, in the same way as biological replication. Rather than one perspective being right and another wrong, different kinds of insights can be realized by examining problems of cultural variation and change from multiple frames of reference. From this approach, behavioral plasticity and Darwinian evolution provide alternative explanations for the same phenomena, but from different frames of reference. One does not necessarily preclude the other. In fact, the different perspectives can be quite complementary. Studies from the biological perspective of behavioral plasticity can serve to document aspects of the environment of cultural replication and interaction. On the other hand, studies of cultural replication and sorting from a Darwinian perspective can provide insight into how and why people can behave in ways that have no impact on or run counter to their own biological reproductive success, or that of their close kin. Unfortunately, this kind of cooperation has been inhibited by adherence to unnecessarily restrictive frames of reference, mainly that of the biology, and a controversy over the role of human intentionality in cultural change.
Intentionality
One of the most contentious issues in the debate over the applicability of the Darwinian process to explaining cultural change involves the role of human agency, or intentionality in determining the course of cultural change. People's abilities to manipulate symbols, pursue goals, possess agendas, subscribe to ethical and moral codes, rationally calculate options, and weave mental scenarios have made most social scientists extremely uncomfortable with the notion that the Darwinian process adequately models the causes of cultural change. The root of this uneasiness lies in a belief that people direct the course of most cultural change through their own agency, which usually involves purposeful innovation and decision- making. If people can respond appropriately to problems they face by creating new behaviors and technologies, or choosing among various known alternatives, then there is little or no causal role for selection and other sorting mechanisms in cultural change. Instead, human agency guides behavior in biologically adaptive (e.g., Boone and Smith 1998; Smith and Winterhalder 1992), cognitively determined (e.g., Barkow et al. 1992; Mithen 1997, Pinker 1997), or culturally meaningful (e.g., Geertz 1973; Hodder 1986; Sahlins 1976) directions prior to the action of any sorting mechanisms. Although many acknowledge that human intentionality arose through a Darwinian process, once this unique cognitive ability was in place, Darwinian evolution was superseded by a variety of psychological, social, political, economic, ecological, and historical processes.
Despite the intuitive appeal and overwhelming belief in the significant role of human intention in cultural change, various philosophical, methodological, and empirical arguments have been made against a causal role for intention. Following Sellars's (1962) distinction between manifest (intentional) and scientific images of man discussed briefly in Chapter 1, Dunnell (1980, 1992) rejects intention, or reason- giving, as unscientific because the empirical entities under investigation are their own cause. Scientific causation, on the other hand, is mechanistic and supplied by theoretical concepts and units, which exist outside the phenomena to be explained. Dunnell further argues that this distinction is fundamentally philosophical, and not open to empirical evaluation. Consequently, one must choose between these different approaches to explanation. However, by choosing intentional over theoretical explanation of cultural phenomena, one is committed to an unscientific approach because it is extremely difficult, if not impossible, to observe intentions. Thus, the methodological requirement of science that knowledge claims be empirically testable cannot be met with intentional accounts. Marvin Harris (1979) also finds empirical support for the primacy of behaviors and their relationships and consequences over motivations or intentions as causes of cultural dynamics. Harris cites the high frequency of independent inventions and inventive insights not actualized until much later as evidence that it is the behavioral and material nexus in which one finds himself that determines his motivations and intentions rather than the other way around. Dunnell offers an alternative to intentional explanation that emphasizes the consequences of behaviors rather than their motivations. Dunnell (1978a, 1978b, 1980, 1989, 1992) and others (e.g., Lyman and O'Brien 1998; O'Brian 1996; Rindos 1984, 1989; Teltser 1995) argue for a strictly Darwinian approach in which behaviors are seen as subject to selection by affecting the fitness (biological reproductive success) of the people involved, or selectively neutral and subject to stochastic mechanisms of drift. Although ambiguous and inconsistent statements exist (e.g., Lyman and O'Brien 1998:644), it appears that Dunnell's evolutionary approach restricts the role of human intention in the Darwinian process to that of generator of behavioral variation. The relative success of these behavioral variants is determined by the working of various sorting mechanisms, not by the intentions that generated them.
Clearly, compelling arguments exist on both sides of this debate over the causal significance of human agency, and there seems to be little or no basis for finding any common ground. Resolution of this debate is further impeded by the fact that we still have a very limited understanding of the roots of human agency, such as how brains think and the nature of consciousness. However, recent studies in philosophy and the cognitive and neurological sciences indicate that our intuitive, common sense understanding of human agency is not particularly accurate (e.g., Calvin 1996a, 1996b; Dennett 1991, 1995; Gazzaniga 1998). To explore the implications of these findings for the issue at hand, let us look more closely at two problems, the creation of novel variants and decision-making, and their roles in directing the course of cultural change.
As an aid in considering these issues, think of all the possible solutions to any problem as a undulating landscape arrayed in order of similarity, and in which better solutions occupy higher positions and worse solutions occur in the valleys. This is a common metaphor in biology where species and other biological entities are arrayed on a landscape, with the height of different points determined by the fitness conferred by that particular configuration ( Dawkins 1996; Dennett 1995; Eigen 1992; Kauffman 1993, 1995; Wright 1932). From this perspective, biological evolution is seen as a hill climbing process, in which blind mutations and genetic recombination explore the landscape and selection pushes populations to higher peaks. If the fitness consequences of different trait configurations are highly correlated because of functional, structural, and semiotic interrelationships, as is the case with biological entities, then the fitness landscapes can be quite rugged with many local peaks ( Kauffman 1995). Under these conditions of blind, incremental variations and rugged fitness landscapes, Darwinian evolution tends to be only locally maximizing and progressive because populations become trapped on local peaks.
From this landscape perspective, the notion that human agency circumvents Darwinian evolution stems from the belief that intention results in cultural change being more globally maximizing than biological evolution. If, through intention, people can perceive the landscape from a global perspective, they can identify and choose the most advantageous options, even if this involves incurring short-term losses on the way to achieving higher long-term gains. Thus, intentionality, rational calculation, and other features of human cognition allow people to move off local peaks to scale higher peaks in the landscape of possibilities. Cultural change, in this view, involves directional shifts that are guided by our abilities to model fitness landscapes based on personal experiences, and the experiences of others (including ancestors and contemporaries), the latter of which are transmitted both culturally and genetically.
Now, we can evaluate this perspective is several ways. Let us look at the problem of creating novel variants first. In the landscape perspective, when people think or do something new, they are moving onto parts of the landscape that had previously only been possible, not actual. How do people know what lies beyond their accumulated experience, the actual? One might be able to use experience, knowledge of certain parts of a landscape, to project into the unknown space of possibilities. However, there are severe limits to this type of inductive reasoning which have been elucidated most profoundly by the eighteenth century Scottish philosopher David Hume. Hume recognized that our limited sensory experience of the external world could not induce general knowledge of that world. This insight shook the foundations of the empiricist, instructionist view of knowledge growth made popular a century earlier by the philosophical writing of Francis Bacon and Isaac Newton's advances in physics ( Cziko 1995; Musgrave 1993).
Deductive reasoning, on the other hand, can yield knowledge, predictions, of the form of landscapes beyond our experience. Hence, it is not surprising that modern philosophers and scientists rely very heavily on deductive logic as they explore the unknown. However, even in these highly intentional, goal directed, deductive enterprises, globally progressive, directional change has been extremely difficult to attain ( Cziko 1995; Hull 1988b; Popper 1959).
A more realistic view of most innovation and invention is that it is blind ( Campbell 1974; Cziko 1995; Dennett 1995; Popper 1979). This does not mean that new knowledge cannot arise from a search process, or that some search processes are not better than others. Striving to solve a problem, and using strategies such as deduction, correlation, metaphor, and analogy are all likely to speed up the process of creating novel, useful solutions. However, even when we take these approaches to problem solving, we are still faced with the dilemma that we cannot know what we do not already know. Consequently, even highly structured problem solving situations involve blind, random generation of possible solutions. For example, take a simple crossword problem. We know from the nature of the problem how many letters that are in the word we need to solve, and the rough meaning or context of the word. We may also know what some of the letters in the word are. To solve this problem, we guess at various possible words, and then test them against what we already know. If the correct word is part of our realm of experience, we can eventually solve the problem. However, if we do not know the word, say the puzzle is in a foreign language, the problem becomes much more difficult to solve.
Although humans are particularly adept at problem solving, and have developed many strategies for speeding up the innovation process, building new knowledge still presents us with significant challenges. Consequently, most novel cultural variations involve short, somewhat random explorations of unknown landscapes at the fringes of our experience, and large jumps are extremely rare ( Basalla 1988; Burke 1978, 1995, 1997). Thus, the notion that, by thinking hard to generate novel, appropriate solutions to perceived problems, people have removed cultural change from the Darwinian process, does not appear to stand up to scrutiny.
However, what of our ability to decide among known, actual alternatives? Does this not short- circuit the Darwinian process of replication, variation, and sorting? Is this not the essence of free will, that we have the power to make decisions, wisely or foolishly, regarding a given course of action, and thus, determine the course of history? Here again, our intuitive common sense provides a very poor basis for understanding. Our ability to be consciously self-aware has engendered a dualistic mind-body, nature- culture view of human existence. Common sense leads us to believe that there is a "self", someone inside us who is in control, making decisions, directing action. However, this dualistic, homuncular view of conscious decision-making is flawed both logically and empirically ( Dennett 1991, 1995; Gazzaniga 1998; Hoffmeyer 1993).
Cognitive and neurological research have demonstrated that there is no single part of our brain responsible for processing all input and directing all output ( Dennett 1991). Instead, our brains work through distributed, parallel processing, out of which consciousness appears to emerge ( Minsky 1985). A large contributor to emergent consciousness is a functional part of the brain, located in the left hemisphere, that creates a post hoc, running narrative out of our behavior and cognition ( Gazzaniga 1998). In other words, our brains process stimuli and make decisions before our conscious selves know about it, and our interpreter, as Gazzaniga calls it, makes sense out of the results by tying them together into a coherent narrative. Consequently, our conscious self-awareness has almost no access to how we actually make decisions, and constructs the sense of "self" to fill this void.
If you doubt that this is the case, consider the problem of speech, either speaking out loud or to yourself. Do you know what you are going to say or think before you say or think it? No. Yet, we have no difficulty speaking in complete, grammatically correct, understandable sentences. How does this happen? In fact, we do think about speech before speaking, but this mental processing is not part of our conscious self-awareness. We do not know about, or become aware of what we think until after the thinking has occurred. The vast majority of our mental processing occurs "behind the scenes" of our consciousness, including most decision-making. If we are not aware of how we make our decisions, how can we, the conscious self, possibly be in control of them? In the absence of coherent theory and deductive reasoning, our interpreter constructs reasons for our decisions and actions that fit in with the running narrative. If we take these post hoc, accommodative reasons as viable scientific explanations, we are likely to be seriously misled.
On the other hand, denying mental processes a significant causal role in cultural change is also not the answer. Rejecting the importance of mental phenomena requires that we continue to see the world in dualistic terms, but favoring the body/nature side of the dichotomy in stead of the mind/culture side. Saying that our reasons are probably not good scientific explanations is not the same as saying our reasons are irrelevant. Although some have taken the extreme position that how and what people think is unimportant for explaining cultural change (e.g., Jones et al. 1995; Lyman and O'Brien 1998; O'Brien 1996a; O'Brien and Holland 1990), I do not.
Exactly how these aspects of human cognition are relevant can be clarified by considering decision-making in light of the Darwinian process rather than as an argument against a Darwinian model of cultural change. As I discussed earlier, decision-making can be seen as a Darwinian sorting mechanism if we shift the frame of reference to the concepts, behaviors, and artifacts being chosen, rather than the individual person involved in the choosing. From these alternate frames of reference, the cognitive processes involved in decision-making are part of the environment of the cultural replicators and interactors. Cultural replicators that are most fit in the human cognitive environment tend to out replicate those that are less fit resulting in what has been termed vicarious or cultural selection ( Cziko 1995; Deacon 1997; Durham 1991; Rindos 1985). The interpreter part of our brain that generates narrative reasons for our past actions also aids vicarious selection by enabling the construction of scenarios for future action that can compete and die in our stead. In this way, decision-making can limit and provide direction for behavioral variation. As long as some behavioral variation continues to exist, the constraining effects of selection at other scales, or frames of reference does not preclude a Darwinian analysis of behavioral changes as well. Thus, rather than negating the importance of cognitive processes in cultural change, adopting a Darwinian perspective helps clarify the role of decision-making in cultural evolution.
However, if there is no "self" doing the selecting, how does cultural selection work? Unfortunately, cognitive research has not yet supplied any firm answers to this question, but three different models exist. These models can be termed innatist, connectionist, and Darwinian. In the innatist model, our brains are thought to contain numerous domain or problem specific modules constructed of neural networks capable of symbolic processing, and designed by natural selection during the evolution of our species ( Barkow et al. 1992; Brown 1991; Cosmides 1989; Lumsden and Wilson 1981; Pinker 1994, 1997).
Particular stimuli cause specific cognitive modules or algorithms to be invoked resulting in certain behavioral and psychological outcomes or decisions. Because these cognitive modules are thought to have evolved during the early history of our genus and species, the decisions produced by these cognitive structures do not necessarily enhance biological reproductive success under the radically different conditions of modern and recent human existence ( Maschner 1996b; Symons 1992; Tooby and Cosmides 1992). Although these cognitive modules have yet to be identified in concrete neurological terms, considerable behavioral and psychological evidence exists that strongly suggests some evolved, innate structuring of human decision-making ( Pinker 1997).
The connectionist approach eschews innate cognitive modules in favor of learned decision rules accomplished by the conditioning of neural networks through the random addition and selective removal of neurons and the selective strengthening of neuronal connections ( Edelman 1987; Elman et al. 1996; McClelland et al. 1986; Rumelhart et al. 1986; Seidenberg 1997). Experience with the world is the main force in conditioning our neural networks, and thus, we can learn how to do and think about things that involve recurrent aspects of our environment. Although neural networks that can learn complex patterns, including decision rules for grammars, have been developed in computers, it remains unclear whether the connectionist approach accurately models actual human cognitive processes, or can accomplish the full range of cognition displayed by people.
In the Darwinian model, well documented patterns of neuronal connections in the neocortex forms the basis for the differential replication of hexagonal arrays of synchronized neuron excitations that code for objects and ideas ( Calvin 1994, 1996a, 1996b; 1998 Calvin and Ojemann 1994). Pyramidal neurons in the upper layer of the neocortex have axon connections to neighboring neurons at a patterned interval of about 0.5 mm, skipping neurons in between. It is this regular pattern of horizontal neuron connection that creates the possibility for synchronized arrays of excitation. These ephemeral, spatio-temporal patterns of neuron excitation expand across areas of the neocortex until the original stimulus disappears, or they encounter other arrays of synchronized excitation. When these encounters occur, the patterns may compete with one another for territory, or spawn new patterns of excitation. Those patterns that are most successful in these copying competitions form the basis of decisions and provide raw material for our conscious experience.
Of course, each of these models is more intricate and subtle than I have been able to present in these thumbnail sketches. The important thing to recognize for our purposes is that these different models are not mutually exclusive, but can complement one another in significant ways. If each of these models accurately represents different aspects of cognition, the combined power for decision-making is quite remarkable. Innate cognitive modules may form the basis for many routine decisions, but the connectionist and Darwinian models enable our brains to create and learn novel decision rules that can greatly extend and alter our genetic dispositions. This multifaceted cognitive environment contains many niches and opportunities for exploitation by cultural replicators. These replicators might first evolve by resonating with innate rules ( Ridley 1997), but, over time, can move well beyond what is good for the genes ( Boyd and Richerson 1985, 1992; Dennett 1990, 1995, 1998).
Superorganic
Even if the unique aspects of human cognition do not exclude cultural change from the Darwinian process, what of the evolution of societies in general? It is generally, though not universally (e.g., Yoffee 1993, 1994), agreed that archaeological research has documented that the general course of cultural change has, for the most part, consisted of directional, developmental growth, with most human societies becoming progressively more complex over time (e.g, Blanton et al. 1993; Carneiro 1978; Flannery 1995; Harris 1979; Rosenberg 1994; Spencer 1997; Trigger 1998). In contrast, the common view of Darwinian evolution is that it is opportunistic, and lacking in overall direction, at least since the first development and diversification of multicelled organisms during the Cambrian (e.g., Gould 1989; Jacob 1982; Lewontin 1982:165). Does this distinction in the trajectories of cultural and biological evolution indicate that cultural change at the higher scales of institutions and societies involves a different process than Darwinian evolution?
From very early on, anthropology and sociology have included a concept of human societies as functionally integrated systems, the superorganic view, based on an analogy between societies and biological organisms ( Garbarino 1977). Although this view has been expressed in a wide variety of ways ( Spencer 1997; Trigger 1998; Wilson and Sober 1994), a common feature is the notion that institutions and societies are not simply the sum of the psychological and behavioral characteristics of the people that participate in them. In other words, these larger scale sociocultural entities constitute emergent functional systems that are composed of the beliefs and actions of individual organisms. However, particular patterns of variation and trajectories of change of the systems cannot be explained solely in terms of the individual behaviors and beliefs.
For the purposes of this discussion, there are two important, interrelated points in the superorganic notion. If the behaviors and beliefs of individuals exist within a web of functional relationships, both metabolic and semiotic, at higher scales, then changes in individual traits are likely to be strongly influenced by the nature of those higher order relationships. Developments in social theory ( Archer 1982; Bourdieu 1977; Brumfiel 1992; Giddens 1979, 1984; Hodder 1986) and complexity theory ( Axelrod 1997; Kauffman 1995) have clarified the dialectic relationships that exist between individuals and society. The actions of individuals are both enabled and constrained by their position in relation to other actors with whom they interact. Higher scale structuresÑinstitutions, societies, etc.Ñemerge from and, in turn, structure these individual relationships. If these higher scale sociocultural entities change in ways other than through a Darwinian process, then their influence on smaller scale entities could severely limit the explanatory power of the Darwinian process with regard to cultural change generally.
The overall directionality of cultural change toward more complex, larger scale entities has led many scholars, beginning with August Comte and Herbert Spencer in the nineteenth century, to argue that cultures change by process of growth similar to that of biological organisms ( Trigger 1998). Frequently, this notion has been expressed in the form of stages of cultural development, with a variety of different stages and developmental goals having been proposed. In addition, a variety of mechanisms have been suggested for the transformation from one stage to another, including various innate human drives, contradictions and conflicts within societies, and homeorhetic, deviation amplifying responses to external conditions.
Recently, these stage-based, developmental views of cultural change have been strongly criticized for a variety of reasons. These include the questionable empirical standing of the societal stages and types, the logically vacuous and ethnocentric nature of the notion of progress, and their failure to recognize the importance of chance and historical contingency in cultural change (e.g., Dunnell 1980; Hodder 1982, 1986; Leonard and Jones 1987; McGuire 1992, 1994; Spencer 1997; Yoffee 1979, 1993). From a Darwinian perspective, the mere presence of directionality of change does not preclude the applicability of the Darwinian process as I have presented it here. Selection mechanisms, including decision-making by individuals and competition among social groups, can result in directional changes at various scales. By shifting our frame of reference and recognizing the potential for causal influences between different frames of reference, it may be possible to generate Darwinian accounts of cultural change at a variety of scales. However, the Darwinian process can also generate functional entities that change by means other than the Darwinian process. Biological organisms are just such entities. Consequently, the applicability of the Darwinian process to some aspects of cultural change does not preclude the operation of other process of change as well. Although this is an area in serious need of more theory building, ultimately, the explanatory relevance of different models of change must be determined by the formulation and testing of alternative hypotheses derived from different models. At this point, however, there does not appear to be any reason to eliminate the Darwinian process from consideration as a viable model of cultural change.
Multiple Frames of Reference and Evolutionary Explanation
Now that we have addressed the objections to a fully Darwinian view of cultural change and finding ample reason to proceed with a Darwinian approach to the problem of corrugated pottery, it is appropriate to turn to the question of how one should go about constructing Darwinian explanations. The most important insight to be gained from the discussion thus far is that what appears to be an example of non-Darwinian change from one frame of reference often becomes Darwinian when we shift the frame of reference. Alternative frames of reference can exist vertically within a hierarchy of replicators and interactors, or horizontally among different kinds of entities at the same hierarchical level. Rather than assuming that a single frame of reference is privileged, a priori, or that there is even only one relevant hierarchy, adopting a more flexible approach to frames of reference forces us to be more clear and precise about the causes of change.
If numerous, potentially valid frames of reference exist for any given problem, how does one determine which frame or frames of reference are causally relevant in a particular case? One way to do this is by answering the question "which entity or entities benefit?" Within a Darwinian context, the entity or entities identified as beneficiaries of some action must also fill the role of replicator. As Dennett (1998) points out "[a] benefit by itself is not explanatory; a benefit in a vacuum is indeed a sort of mystery; until it can be shown how the benefit actually rebounds to enhance the replicative power of a replicator, it just sits there, alluring, perhaps, but incapable of explaining anything." By admitting the possible causal relevance of multiple frames of reference, we recognize that there are many potential beneficiaries. Both biological and cultural replication can take place through a wide variety of replicator entities. In the context of cultural evolution, these range from genes and memes (including ideas, behaviors and artifacts) at the lowest hierarchical level, through organisms or persons (generated by a complex of genes and memes), to populations and larger-scale sociocultural systems (institutions, societies, etc.) at the highest hierarchical level.
When constructing explanations of particular phenomena, we must realize that there may be complex relationships among different replicators such that one benefits at the expense of others (parasitism), one benefits at no cost to another (commensalism), or there are multiple, simultaneous beneficiaries (mutualism). Hierarchical relationships can also come into play with the entities and processes at one level enabling, constraining, or entraining entities and processes at other levels. Commenting on the impact of considering multiple frames of reference in biological evolution, Vrba and Eldredge (1984:165) note that "[t]hinking hierarchically forces consideration of precisely at what level a causative process is lodged, precisely what its up- and downward causes may be to other levels, and precisely which individuals bear the characters that lead to differential sorting."
Currently, most evolutionary approaches in the social sciences have focused on a single or very limited set of frames of reference. For example, sociobiology concentrates on genes and genetically determined behaviors, evolutionary psychology centers on innate cognitive architecture, behavioral ecology and cultural transmissionism focus on the innate and learned decision rules of organisms, evolutionary archaeology fixes on biological populations, memetics centers on socially learned ideas, behaviors, and artifacts, and processual approaches tend to concentrate on sociocultural systems. As I have tried to make clear, none of these approaches is necessarily wrong, but they are all incomplete. Incorporating multiple frames of reference into our theory of cultural evolution not only clarifies the importance of the Darwinian process in cultural change, but provides a basis for integrating, and potentially unifying the currently disparate bodies of theory in the social and natural sciences.
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