Pre-Publication Version. Full bibliographic reference: Frank, Roslyn M. 2009. “Shifting Identities: Metaphors of discourse evolution.” In: Andreas Musolff and Joerg Zinken (eds.), Metaphor and Discourses, pp. 173-189. Palgrave MacMillan. Shifting identities: Metaphors of discourse evolution Roslyn M. Frank University of Iowa Email: roz-frank@uiowa.edu 1. Introduction. Evolutionary models of discourse history that follow a Complex Adaptive Systems (CAS) approach and emphasize socio-cultural situatedness of discourse metaphors aim to avoid some of the pitfalls of more genetically inspired linguistic models that include linguistic counterparts of DNA or even the genes/memes/lingueme analogical sequence, with the result that the heuristic of the biological source tends to excessively control the conceptual shape of the resulting analogically conceived linguistic target. In this chapter we explore epistemological and methodological aspects of these contrasting paradigms, concluding that more attention to context and agency is needed when appropriating these genetically inspired models, while the adoption of a CAS framework could produce a larger, more expansive conceptual platform for research into discourse metaphor networks. Over the past two decades developments in the field of cognitive science have brought together pre-existing methodologies and theoretical approaches from a wide variety of disciplines and at the same time promoted cross-disciplinary dialogue relating to the development of new methodologies and theoretical frameworks (Bono, 1990; Maasen and Weingart, 1995, 2000). This cross-fertilization has been particularly rich in the case of researchers concerned with modelling ‘language‘ and ’language change‘ in a number of new settings, for example, those involved in working with artificial distributed agents associated with research projects in Artificial Intelligence (AI) and Artificial Life  2 (A-Life), as well as in the area of ecolinguistics, biosemiotics and theoretical biology. Whereas a great deal of attention and effort has been focused on developing these models in various subfields of cognitive science, to date less work has been carried out by Cognitive Linguists in terms of attempting to model the entity comprised by ‘language’ through cross-fertilization with the evolving methodological and theoretical models found in the ‘hard’ sciences, for example, Complex Adaptive Systems theory (CAS). Nonetheless, in recent years a number of important steps have been taken in this direction, e.g., Croft (2000), Steels (1999) and most recently, Sharifian (2003, 2008; Frank, 2008a). These initiatives represent a conscious move away from the linear, Cartesian- Newtonian mode of thinking and the linear conceptualization of causality characteristic of earlier models of ‘language’ and ‘language change’ and, as such, these steps represent movement toward (re-)descriptions of the phenomenon of ‘language’ more in terms of a self-organizing, dynamic system. The notion of a self-organizing, dynamical system is central to Complex Adaptive Systems (CAS) theory, also known as Dynamical Systems theory (see Clark 1997). Recently another avenue has opened up for applications of CAS thinking, namely, the potential that this theoretical framework has for the analysis of discourse metaphors. The latter are defined as ‘relatively stable metaphorical mappings that function as a key framing device within a particular discourse over a certain period of time’ (Zinken, et al., 2008). The present chapter focuses first on the applications of CAS thinking to the notion of discourse metaphor networks. Then, an exemplary analogical sequence is explored: the evolution and discourse career of a biological concept, namely, that of the ‘gene’. Although this term first appeared at the beginning of the twentieth century, only in the past decade has it started to penetrate the discourse of Cognitive Linguistics and Critical Discourse Analysis, revealing at the same time its ability to generate extended metaphor formations in the linguistic sciences. More concretely, I will discuss several analogical expansions of this base concept of a ‘gene’, showing how they currently function as a productive source for heuristic inferences in contemporary discussions of language and language change, particularly in the case of those attempting to incorporate an evolutionary or Neo-Darwinian perspective into their overall explanatory model for  3 language evolution or language change, sometimes referred to as a ‘population approach’ where ‘language’ is treated, analogically, from the perspective of a ‘species’ or ‘population’. Discourse metaphors provide evidence for the socio-cultural situatedness of metaphorical reasoning along with the characteristic features of context-boundedness, strategic fuzziness, and polyvocality. As others have shown, discourse metaphors often demonstrate a rich social and cultural history. They can also exhibit an uncanny conceptual staying power, which reflects their status as highly entrenched, albeit constantly changing, entities, given that the socio-cultural ground under them is always shifting (Chilton, 2005; Frank, 2003, 2005, 2008a; Nerlich and Hellsten, 2004:262; Zinken, et al., 2008; and the contributions by Banks, Cowling, Musolff and Zavadil in this volume). Hence, discourse metaphor analysis brings to the fore the importance of a diachronic perspective with a cultural orientation, where continuity is apparent in the cognitive patterns manifesting themselves in such a longitudinal analysis. This set of conditions allows the discourse metaphor formation or analogical network to interact and hence co-evolve with its socio-cultural environment. On the one hand, this socio-cultural embeddedness acts to provide stability for the network in question, i.e., there are cognitive constants that seem to be discursively embedded in a relatively stable reservoir of cultural beliefs and social representations. On the other hand, these environmental factors can act to destabilize the dynamics of the construct, given that discourse metaphors simultaneously provide sites for conflict, resolution and cooperation on the part of the language agents. In sum, the meanings associated with a given discourse metaphor are socio-culturally situated and co-evolve in conjunction with the cultural constructs in which it is embedded (Zinken, et al., 2008; Musolff, 2004; Frank et al., 2008b). In this sense, the stability of the discourse metaphor depends, at least to a substantial degree, on the nature of the coupling that takes place between the discourse metaphor network and other cognitive artefacts, for example, the socio-cultural resources that are available, internally and externally, to the language agents themselves. In order to examine the dynamics inherent to this process we can begin by looking at the advantages of incorporating a Dynamical Systems theory view  4 (see Clark, 1997: 80–123) and, more narrowly, by reflecting on the benefits of adopting a CAS model as a tool for exploring the functioning of discourse metaphors and analogies. 2. Overview of Complex Adaptive Systems thinking Complex systems are systems in process that constantly evolve and unfold over time. Change is an integral element of their functioning. In the case of complex adaptive systems (CAS), a subset of dynamic nonlinear systems, they are adaptive in that they have an innate capacity to change and learn from experience, so to speak. Thus, they are endowed with the ability to evolve and adapt to a changing environment. Examples of CASs include social insect and ant colonies, the biosphere and the ecosystem, the brain and the cell, the immune system, financial markets, social networks, the Internet and also, in general, any human social group-based endeavour forming part of a cultural and social system. Thus, since CASs arise in a wide range of contexts, this theoretical framework is rapidly gaining ground in a variety of disciplinary areas, not only in the biological and physical sciences (Lansing, 2003:183), but also the social sciences, and to some extent as a tool for the study of artificial and natural language evolution, particularly in the field of field of ‘evolutionary linguistics’ (Steels, 1999, 2004). Broadly defined, a CAS is a system that is self-organizing in which there are multiple interactions between many different components while the components themselves can consist of networks that in turn operate as complex (sub)systems. CAS thinking is concerned with understanding the global behaviour arising from local interactions among a large number of agents. This global behaviour or emergent dynamics is often quite complex; it is neither specified by prior design nor subject to centralized mechanisms of control, and, consequently, it is often difficult or impossible to predict solely from knowledge of the system's constituent parts what the emergent global level properties of the system will be. Therefore, the basic characteristics of a CAS include the following: (1) it is constantly constructed and reconstructed by its users; (2) it is self-organizing; and (3) it is characterized by multiple mechanisms of control, that is, control is distributed throughout the system rather than residing in a single centralized command and control centre.  5 Furthermore, in such a system ‘global order’ derives from local interactions. Hence, when we apply the CAS theoretical model to natural language and/or, less expansively, to the cognitive networks that underlie discourse metaphors, the overall system can be viewed from two perspectives at the same time: • from the local level, which allows for description and analysis of the activity of the (individual) language agent and her cognitive architecture (idiolect + the socio-cultural situatedness of the agent herself, viewed as embedded in and, hence inseparable from, the influence of an environment that itself is subject to constant alteration); • from the global level, which allows for the description and analysis of the global order while the latter, in turn, is the result of the combined activities of heterogeneously distributed agents over time. Briefly stated, discourse metaphor networks can be understood methodologically as examples of complex adaptive systems, constantly in the process of being constructed, deconstructed and reconstructed by language agents, and in which there are multiple interactions between many different components. In order to understand the functioning of the system, we need to remember that the emergent phenomenon described above has a strong causal impact on the behaviour and learning of each individual language agent. Consequently, there is a kind of ‘circular causality’ operating at all times that forms an intrinsic part of the system (Steels 1999). At the local level, the behaviour of individual language agents determine ‘language’, that is, their choices act, cumulatively, to determine (emergent) language structure understood as operating at the global level. At the same time, when viewed from the local level the resulting emergent global-level structure co-determines the range of behaviours of the agents, that is, it acts to constrain and shape their interactions at the local level. In summary, circular causality is a fundamental aspect in the functioning of language and the constitution of discourse metaphors and is not unusual in other types of living systems which are themselves self- organizing and complex in nature. Therefore, a fundamental goal of research models designed for the study of natural languages, evolutionary change and metaphor formation is to gain an understanding of these bottom–up and top–down exchanges between local  6 and global levels of a complex system, as each provokes emergences and constraints upon the other. 3. Shifting perspectives: genes, memes and linguemes Until recently the CAS approach to language has been more widespread as a model in the field of ‘evolutionary linguistics’, most particularly in computer simulations of the evolution of language, rather than as part of the theoretical toolkit of Cognitive Linguists examining natural language(s). So, the next logical step would seem to be its design application to the problems facing ‘evolutionary cognitive linguistics’ where explorations of natural language processes would be the goal, including those involving discourse metaphors. Here the CAS model could help reduce or even alleviate certain conceptual complexities, or perhaps better stated, drawbacks, that are inherent in some of the more recent ‘gene-centric’ or ‘meme-centric’ models often found alongside ’species-centric‘ and ’population-centric‘ models of language (Chilton, 2005; Croft, 2002, 2006; Deacon, 2004; Mufwene, 2001, 2005; Steels, 2004). These approaches, particularly those most influenced by ‘memetics’, can be viewed collectively as a kind of discourse metaphor in evolution for they tend to appropriate the notion of agency attributed to the concept of a ‘gene’. Except in the most unusual of circumstances, one would not expect the expertise of linguists to be in the field of molecular biology nor would one expect them to have a familiarity with the evolution of the concept ‘gene’, a concept that I suggest can be viewed as an analogy that has its own long and complex history. Rather, I believe most would agree that the intersection of these disciplinary discourses results from the way that metaphors regularly act as ‘messengers’ propagating themselves across disciplines (Maasen and Weingart, 1995). At times it has been the field of linguistics that has contributed to the metaphoric repertoire of the ‘hard’ sciences, and at other times the analogies have moved in the opposite direction (Frank, 2008a). In short, adopting a CAS perspective provides us with a means of tracing the heuristically productive role of these biologically inspired metaphors, e.g. the use of ‘species’ analogies (Mufwene, 2001, 2005) as well as Croft’s Generalized Analysis of Selection model with its ‘linguemes’ (as linguistic counterparts of ‘memes’) and ‘lineages’ (Croft, 2000, 2002).  7 The CAS model brings new conceptual tools into play and, at the same time. it also allows for continuity with another emerging avenue of research, namely, attempts at reformulations of the meaning of a ‘meme’ and more broadly of the field called ‘memetics’. Following Dawkins (1976, 1982, 1991), a ‘meme’ refers to a unit of cultural information that is transferable from one mind to another: a unit that leaps from one mind to another. For Dawkins, examples of memes are ‘tunes, catch-phrases, beliefs, clothes fashions, ways of making pots or of building arches’ and ‘[j]ust as genes propagate themselves in the gene pool by leaping from body to body via sperms or eggs, so memes propagate themselves in the meme pool by leaping from brain to brain’ (Dawkins, 1976: 192). In its popularized version, the memetics framework is assumed to hold that a meme: propagates itself as a unit of cultural evolution and diffusion—analogous in many ways to the behavior of the gene (the unit of genetic information). Often memes propagate as more-or-less integrated cooperative sets or groups, referred to as memeplexes or meme-complexes. […] Proponents of memes suggest that memes evolve via natural selection—in a way very similar to Charles Darwin’s ideas concerning biological evolution—on the premise that variation, mutation, competition, and ‘inheritance’ influence their replicative success. (Wikipedia 2007)1 This ongoing process of reformulation of the basic tenets of memetics is encountered in the work of linguists such as Musolff (2004, 2008), Chilton (2005) and Croft (2002) as well as in Mufwene (2001, 2005). Researchers in adjacent disciplines of cognitive science, have noted that the concept of a ‘meme’ needs to be fleshed out; that as a concept it is vague, lacking in specificity and that it operates with a misplaced sense of agency (Gatherer, 1998; Wilkins, 2005). Deacon (2004) has observed that 1 For a similar, although strictly academic discussion of “meme agency”, cf. Heylighen, 1998.  8 [t]he core problem of this theory [of memetics], I think, is a kind of misplaced agency, that gives the impression that both genes and memes—replicators—can be understood without considering their embeddedness in a dynamic system which imbues them with their function and informational content. This, then, is not just a problem with memes, but a problem with the replicator concept in general, inherited from Dawkins’ short-circuited description of information processes in biology. (Deacon, 2004: 20) Deacon is far from alone in his rejection of the ontological grounding and misplaced agency attributed to the replicator concept, genes and memes in general. For example, speaking about the ‘trendy talk about the selfish gene also known as “the replicator”’ (Moss 2004: 174), Moss observes that for Dawkins and his epigones it is the parasite [selfish gene] that invents the host […..]. Dawkin's selfish replicator constitutes the quintessence of conflationary confusion. His viewpoint does not build on the advancing elucidation of molecular biology but rather depends on an enforced ignorance of it. Dawkins and his followers take their conflationary replicator (the so-called selfish gene) as an ontological bedrock. (Moss, 2004: 194) The confusion surrounding the propagation of the analogical sequence that has produced this gene → meme → lingueme series results from the fact that in contrast to proteins, lipids and carbohydrates, the gene ’did not come on the scene as a physical entity at all, but rather as a place-holder in a biological theory‘ (Moss, 2004: 2). Indeed, there never has been a unitary, fixed ‘object’ that acted as a causal agent for replication and transmission of genetic material. Rather the term has always been a place-holder: when the term ‘gene’ was invented, it did not correspond to any real entity, rather it was a hypothesis, albeit a strongly held one, still awaiting scientific verification. As such, it should be viewed as a device that functioned more as a heuristic guiding the direction of research than as having a concrete physical  9 counterpart. Yet for biologists this conceptual notion became so embedded in their (earlier) ways of thinking and more importantly in the popular imagination, that today it is nearly impossible to rid ourselves of these habits of thought (and language). (Moss, 2004: 2) Stated differently, throughout the history of classical and early molecular genetics, the ‘gene’ was generally assumed to be not only a fixed and unitary locus of structure and function but also a locus of causal agency. So, we might argue, ‘it was a way of talking that tacitly grants to “genes” the power to act, even in the absence of any information about how they might act’ (Keller, 2000: 46, emphasis in the original). Hence, from its inception the term ‘gene’ acquired properties of (unitary) materiality, agency, autonomy and permanence. And over time that reified ‘way of talking’, which assumed a context- independent ‘materiality’ for the concept, became commonplace. In contrast, over the past twenty-five years subsequent genomic research has revealed that none of these assumptions are true as they were stated, and that the reality of how genomic material interacts and replicates is far more complex than previously suspected. In some ways, the processes themselves are equally as puzzling to the biologists of today as they were to their counterparts in times past (Moss, 2004). Critiques of the tenets of memetics and its misplaced agency, such as those of Deacon, Moss and Keller, should be understood in light of these observations on the non- materiality of the referent associated with the concept of a ‘gene’. Furthermore, these comments come from members of a given epistemic community and are directed to members of similarly situated interpretive communities who are familiar with the topic at hand and the controversy in question. In contrast, Croft explains his choice of the term ‘lingueme’ to his readers, who are primarily members of a different disciplinary interpretive community, as follows: In order to clearly distinguish the embodied replicator from the structure that it possesses, we must give it a name. Following a suggestion by Martin Haspelmath, I propose that the paradigm linguistic replicator be called a LINGUEME, on the analogy with Dawkins’ meme. Thus, the paradigm replicator in language is the  10 lingueme, parallel to the gene as the basic replicator in biology; an utterance is made up of linguemes, and linguemes possess linguistic structure (Croft, 2000: 28). Citing Hull and Dawkins, Croft draws out additional analogies holding between this view of a ‘gene’ and a linguistic ‘replicator’, explaining that replication is: the process by which an entity (the replicator) produces a copy that possesses a version of inherent structure of the original entity […]. Replication can be normal (identical with the structure of the parent) or altered (not completely identical with the structure of the parent). Differential replication is the replication of a replicator at an increasing (or decreasing) relative frequency compared with other replicators. (Croft, 2000:242) In this respect, we need to keep in mind that the history of the concept of a meme dates back to metaphoric extensions of what today we must view as overly simplistic and outdated definitions of the concepts of gene and gene agency, extensions which are simply no longer viable in the post-genomic era, but rather tied to earlier gene-centred discourses which in turn were based on even earlier variations of preformationist gene concepts, grouped under the rubric of ‘gene-determinism’ (Moss, 2004; Hellsten, 2005; Strohman, 1997, 2001; Hilferty and Vilarroya, 2008). In other words, the notion of agency assigned to the gene during the 1960s and later transferred to Dawkins’ (selfish gene) meme has been called into question by advances in today’s systems biology and related fields of complexity science. At the same time, philosophers of science as well as researchers in the field of biology and environmental science are increasingly attuned to the important role played by extended metaphoric networks in guiding research directions and experimental practices. (see Keller, 2000; Moss, 2004). When Dawkins first came up with his notion of a meme, based analogically and phonetically on gene, biologists still thought that the ‘program’ was in the genes, and then later in the proteins ‘encoded’ by genes. This type of gene-determinism is now being challenged by a broader context- bound model, the ‘new epigenetics’ (Moss, 2004: 52) and shaped by a Complex Adaptive  11 System approach (Strohman, 2001), as well as by a far greater awareness of the complexity of gene–protein–environment interaction (Nerlich and Hellsten, 2004). Consequently, even though memetics was based originally on earlier, and in many senses now outdated, formulations of gene agency, recent attempts by (Cognitive) Linguists to reformulate memetics are both interesting and promising. Their research agendas should be viewed as a means of testing how the highly entrenched and wildly popular term ‘meme’ might be appropriated, expanded and recast, in short, how it might be redefined and appropriated as part of a terminological toolkit that could be employed, for example, when discussing the ‘discourse career of a metaphor’ (Musolff 2004: 70). Musolff proposes converting memetics into a tool for the investigation of metaphor and conceptual evolution. His proposal would bring into view the functioning of ‘conceptual clusters’, roughly equivalent to the ‘nodes’ and ‘networks’ operating in the (sub)dynamics of a CAS modelling of a discourse metaphor formation. Musolff also explores the methodological advantages of employing ‘a metaphor-meme’s point of view’ (Musolff, 2004: 69–71). Other components of such a terminological toolkit might be concepts such as ‘discourse metaphor networks’ (Zinken, et al., 2008), the relationship between collective cognition and individual activity, and the distributed nature of language (Bernárdez, 2008), as well as the heterogeneously distributed nature of ‘cultural conceptualizations’ (Sharifian, 2003, 2008). Over the past decade, population approaches to language have become more common, inspired, in part, by the writings of Dawkins (1976, 1982) with his memes, replicators and vehicles and, later, by Hull (1988) with his discussion and revision of Dawkins’ theoretical framework, specifically, its application to the study of the evolution of primarily scientific concepts, and more concretely, to the way in which the scientific model of a given group of scientists is elaborated and evolves over time. However, along with the diffusion of the concept of the meme has come significant criticism of the basic tenets of memetics, or lack of said tenets, as well as a lack of consensus concerning what a meme actually is and what memetics really stands for as a field of research. Also, the proliferation of studies in which ‘mind viruses’ (Dawkins, 1991) or other forms of ‘epidemiological’ transmission are present, as conceptual frames of analysis, has brought into question the effectiveness of the original gene–meme–virus analogical construct  12 (Deacon, 2004; Gatherer, 1998; Sperber, 1990, 2000; Wilkins, 2005). For example, Chilton has explored the possible applications of the meme and virus analogies to the analysis of metaphor and in the process accepts, at least momentarily, the (misplaced) agency attributed to the gene–meme–virus concept: But here I would hypothesize that conceptual constructs become meme-like and ‘infect’ the mind (under the right social conditions) when they have complex blending potential that recruits fundamental knowledge domains along with the core mechanisms of the metaphor. There is a further ingredient that seems to go along with textualized memes of this kind—the delivery of some kind of credibility assurance and epistemic warrant. (Chilton, 2005: 40) Picking up on the implications of the virus analogy for metaphor studies, Chilton proposes a new name for it, ‘ideational epidemiology’, and then returns to the key question, that of agency: [I]deational epidemiology will study the spread of ideas in the population. Over time the distribution may change—may shrink or spread, so ideational epidemiology will be interested in patterns of spread and retreat. […] Why do some ideas or idea-clusters propagate more than others? (Chilton, 2005: 17) Chilton (2005: 41) concludes his discussion on a more circumspect note, stating that: ‘if there is such a thing as meme propagation one of its main modes of operation lies in the properties of metaphorical expressions […]’. Or, to bring this statement more in line with the arguments laid out in this chapter, we might take it a step further, and assume that the recognizably vague referentiality of the term ‘meme’ is better understood as a kind of ’metaphor‘(in its broadest sense), ‘analogy’ (Musolff, 2004: 56); or a situated ‘cultural conceptualization’ (see Sharifian, 2008). In other words, conceptual constructs, such as metaphors and analogies, are constantly shifting entities, that are constructed, deconstructed and reconstructed as they expand and contract in terms of their spreading activation into new domains or as they retreat from old ones. While these old subsystems  13 can act to build up network connectivity, emergent nodes with slightly new (expanded or contracted) meanings can attach themselves and move into place. And, as Chilton (2005) has suggested, under the right social conditions the end result can be a highly entrenched and enduring discourse metaphor formation. Thus, discourse metaphor network analysis can serve to highlight processes of change, stabilization and destabilization, as well as conflict, in which ‘alternative definitions and perspectives struggle against each other, producing brief and tenuous moments of stasis rather than monolithic, permanent formations. This view of discourse is useful because it recognizes the ongoing tensions and opposing forces, rather than the moments of apparent stability, as the most salient features’ (Henze, 2004: 315), shaping the interpretative strategies brought into play for understanding a given metaphor at a specific juncture in time as well as over longer periods of time. In this way a discourse metaphor can provide a localizable framework of interpretation which, through explicit specification, can be assigned an upper temporal boundary, a point of departure for the analysis of its evolution (Musolff, 2004, 2008). Furthermore, a closer look at the complex interactions taking place in the subdynamics of a given discourse metaphor will reveal how modifications are brought about, and the way that various types of attractors can operate upon each other. In some cases, given the socio-cultural situatedness of the language agents, the resulting environmental resonances may contribute to stabilizations within networks making up the overall meaning-making system. Moreover, a confluence of opinions, beliefs and motives can allow certain nodes to be selected for globalization, that is, discursive prominence can be given to a specific node or cluster of meaning(s) within the formation, e.g., a node produced by the conflation of the notions of ‘language’ and ‘species’ or analogies between ‘memes’ and ‘discourse metaphors’. These shifts in salience are the end result of aggregate actions of individual language agents operating at the local level over time — and these can be integrated into the discourse metaphor formation at a global level. Thus, a discourse metaphor network is not a monolithic entity. Instead, it should be viewed more as a phenomenon whose dynamic structure is always (somewhat) unstable — always in flux — as a result of the continual process of re-negotiation taking place between competing voices, microstructures which in turn must operate in local  14 environments conditioned by the top–down influence of (pre-)existing emergent globalized macrostructures. Stated differently, in the case of discourse metaphors, particularly those used in scientific fields, we need to take into consideration the concrete socio-cultural situatedness of individual language agents and the interpretive (epistemic) communities to which they belong. Because the agents’ situatedness inevitably places them within a given location and time frame, along with the heterogeneously distributed nature of cultural conceptualizations in general, any given set of language agents operating, locally, can appropriate and employ anachronistic interpretive frameworks and/or conceptualizations that are partial or limited in some respect, e.g., ones that are not necessarily shared by members of the ‘expert’ scientific community. In sum, there are different levels of awareness of the historically conditioned use of the terms in question and hence different understandings of their accepted meanings. 4. Conclusions In summary, my general observations concerning ‘gene-centric’ and ‘meme-centric’ analogies and the ‘species’ or ‘population’ models of language should not be understood as a rejection of the views on language change put forward by researchers such as Croft (2000, 2002, 2006) and Mufwene (2001, 2005). Rather, I offer these comments in an attempt to identify ways in which such models might be modified, supplemented and their explanatory power increased by the adoption of the heuristic of complex systems thinking: language conceptualized as a complex adaptive system. Indeed, Croft has already set forth the groundwork for an ‘evolutionary model’ and his own research already integrates many aspects of complex systems thinking. Exactly how this methodological and theoretical revision might be accomplished is beyond the scope of this chapter, although hopefully the topic will be taken up and elaborated upon in more depth in the future. In conclusion, at this stage those of us who are interested in exploring discourse metaphors find ourselves actively engaged in developing a flexible methodology and at the same time endeavouring to construct theoretical framework(s) appropriate for this new subfield of Cognitive Linguistics and Critical Discourse Analysis. This juncture  15 presents us with a unique opportunity to reflect on meta-theoretical issues. It is an opportunity that could allow us to join with the larger community of cognitive scientists who are exploring the role of language in cognition as well as the situated and collectively distributed nature of cognition and language evolution in general, the latter notion being understood as referring both to the origins and evolution of language and to the cognitive and cultural processes that give rise to language change. There are significant benefits that would accrue by adapting a CAS modelling technique for conceptualizing language and more specifically for analysing discourse metaphors. One of the most significant advantages would be the fact that by using a framework whose terminology is already recognized across many disciplines of cognitive science we would obtain a kind of passport that would allow discourse metaphor research to more readily cross these disciplinary boundaries and propagate, hopefully, in a synergistic fashion. At the same time, the adoption and application of CAS terminology and associated concepts, e.g., ‘circular causality’, ‘cultural conceptualizations’ and the ‘extended mind’ (see Clark, 1997; Clark and Chalmers, 1998), to linguistic data would allow us to begin communicating more freely in what is already rapidly becoming the methodological lingua franca of many areas of social and behavioural sciences. Stated differently, the adoption of a CAS framework would produce a larger, more expansive conceptual platform for research into discourse metaphor networks. For those of us who are concerned with discourse metaphor networks and modelling cultural conceptualizations — and their interactive role within language and culture — we are faced with a challenge that does not differ significantly from the difficulties that others have confronted when attempting to model cultural evolution (Sperber and Claidière, 2006; Sperber and Hirschfeld, 2003). Unfortunately, in some studies dealing with evolutionary models of culture, at times the ‘information’ metaphor (found in the ‘conduit’ framework) tends to weaken the logic of the arguments proffered, a process by which there is a reification of an entity called ’information‘ which then is ‘communicated’ or otherwise ‘reproduced’ in what is often a contextual void, a kind of argumentation also typical of memetics which assigns agency to the meme in a false analogy to the agency that is assumed to be located in an entity called a ‘gene’. Moreover, the problems are not simply those related to understanding language change,  16 e.g., the shifts that take place over time in discourse metaphor networks, but also and perhaps more importantly, to discovering the nature of the mechanisms governing the stability of linguistic meaning structure(s); how a particular self-organizing system both adapts and yet at the same time maintains a kind of equilibrium that in turn keeps ‘vital’ structures safely in place and functioning. In sum, CAS thinking, understood as a cross-disciplinary research framework, is in circulation across many subfields within the biological and information sciences and perhaps more importantly, it is gradually gaining ground in many other fields now loosely comprised by the term ‘cognitive sciences’. 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