This article is reproduced here with minor fixes for typographical errors. It was originally published in Critical Meme Reader III: Breaking the Meme (Chloë Arkenbout and İdil Galip, eds., 2024. https://doi.org/10.25969/MEDIAREP/23529). You can download the anthology or order a physical copy free of charge at https://networkcultures.org/blog/publication/critical-meme-reader-iii-breaking-the-meme/

The genic perspective is insufficient not only as a metaphor for thinking about and modelling cultural evolution, but also for understanding biological evolution. The simple rules of Darwinian ‘evolutionary selection game’ mask the complexity of the process underlying it, because evolution is a game that evolves its own rules.

— Eva Jablonka, 2000, pg. 9.

Lack of interest in the mechanism underlying the hereditary transmission of these characteristics is paradoxically also a strength, because it liberates those studies from an attachment to a specific mechanism or heredity.

— Michel Morange, 2007, pg. 55.

Memetics will be what we make it.

— David Hull, 2000, pg. 43.

The central thesis I present here is not new to memetics, at least not to the philosophy of biology: classical (Dawkinsian) memetics is rife with scientific and theoretical problems and must be radically modified (or altogether discarded). What is new here is my claim that the supposed failure of memetics, the interdiscipline, can become a crucial advantage for meme studies, the transdiscipline; and that the temptation of memeology, the multidiscipline, must be resisted (just as we resisted the temptation of sociobiology). The time is right for turning meme studies into an inclusive transdiscipline, given the development of modern data science and the digital humanities, as well as the boom in the sophisticated philosophical understandings of culture and the internet. Yet, data alone is not enough, just as a memetic theory alone was not enough. We need metamemetics, the philosophy of meme studies.

Dawkins’ gene-centric view of evolution was highly influential both within the field of evolutionary biology and with the general public, and debates around Dawkins’ ultra-Darwinism often occupied centre stage in many areas in the philosophy of biology (Sterelny, 2001). While minor, arguably the most well-known (and controversial) aspect of these debates is the Dawkinsian view of cultural evolution, namely memetics. The backdrop to this controversy around memetics is the ongoing, lively debates within the broader field of cultural evolution (Acerbi & Mesoudi, 2015). The background to these debates within cultural evolution are the debates within evolutionary biology itself, in which the concept of the gene has itself remained a case of a ‘floating reference’(Weber, 2005, pp. 223-227), which permits scientists to employ different natural classifications for a nonessential, functional phenomenon as appropriate to their individual investigative perspectives.

The prevailing position among contemporary meme scholars, particularly those with a new media background, is that the meme is an unscientific, albeit highly useful, metaphor. The popularity of this position owes much to the apparently dramatic demise of the Journal of Memetics a mere three years after Bruce Edmonds issued “Three Challenges for the Survival of Memetics”(Edmonds, 2002; Edmonds, 2005); Shifman’s seminal paper, “Memes in a Digital World: Reconciling with a Conceptual Troublemaker”(Shifman, 2013); and Burman’s influential history of ‘meme’ as a popular scientific concept, “The misunderstanding of memes: Biography of an unscientific object, 1976-1999” (Burman, 2012). Cited more than 1000 times (of those, 514 are articles with some variant of ‘meme’ in their title, out of approximately 10000 all such articles published since 2013), Shifman’s article is arguably the most influential work on internet memes, and a founding work of memeology. Shifman advocates for a restrained Dawkinsian perspective, in which biological analogies are to be limited and human agency is emphasized (Her, 2016). Burman is conservative in the other direction, emphasizing that the meme concept is appropriate only within the confines of Dawkins’ original argument, as a metaphor in the context of clarifying the notion of the gene as replicator.

Burman, in a 2016 interview about his 2012 article, suggests that ‘there’s no such thing as a meme’ (The MIT Press, 2016); but also, that memeticists should ‘change their theory of memes to accommodate the change in the meta-theory of genes’; and, that ‘we must distinguish between three very different uses of the word: the original proposal (replicator), the popularization (idea virus), and the contemporary (cat pictures with funny captions).’ There is an apparent tension here between the pull of a powerful concept and the disappointment of discovering that it seems to lack a consistent referent. Marc Tuters echoes Burman by claiming, on the one hand, that ‘meme magic is real but memes are not’ (Tuters, 2021, pg. 46); while on the other hand also arguing that Gilbert Simondon’s ‘coevolutionary theory’ (drawn from media theory, not from evolutionary theory) ‘offers a way out of seeming deadlock.’ The demand for a replacement for classical memetics within meme studies is evident.

I disagree with Burman and Tuters that memes do not exist, or that the ‘original’, ‘popular’, and ‘contemporary’ uses of the meme concept should be distinguished in order to be segregated. But I agree that memetics should be updated to reflect the metascientific developments of the interdisciplinary, constituent sources of memetics. Distinguishing the different meanings of ‘meme’ is an important part of that work. Furthermore, it is not only the various definitions of ‘meme’ which must be distinguished, but also the various conceptions of meme studies. Each of the following are distinct yet interconnected concerns: meme studies as done and understood by meme scholars; meme studies as understood by researchers beyond the discipline; meme studies as popularly understood. These three conceptions of meme studies very roughly correspond to the three modalities of ‘meme’ identified by Burman (contemporary, original, and popular, respectively).

‘Darwin’s separation of ontogeny and phylogeny was an absolutely necessary step in shaking free of the Lamarckian transformationist model of evolution … [yet] Darwinism cannot be carried to completion unless the organism is reintegrated with the inner and outer forces, of which it is both the subject and the object’ (Levins & Lewontin, 1985, pg. 106). Likewise, distancing internet meme studies from cultural evolution was a necessary step in shaking free of the fossilized popular understanding of evolutionary biology, with which memes continued to be analogized.

Piersma & van Gils argue that physiology, behavior, and ecology can be genuinely synthesized, by incorporating lessons from developmental biology and multiple dimensions of inheritance (Peirsma & Gils, 2010). Analogically, meme studies should take up Shifman’s suggestion that we reintegrate subfields which have diverged throughout their development:

Whereas the distinction between memes and virality (as well as their separate modes of investigation) has been functional in the formative stages of these fields, at this phase blurring the lines may move both arenas forward (and perhaps even result in their merger). The study of internet memes would greatly benefit from addressing questions related to patterns of diffusion and influence, while research into viral content would be enriched by delving into the social and cultural meanings that such texts invoke.

— Shifman, 2015.

Each modality of meme concept can tentatively be seen as corresponding to one of three traditions within the lineage leading towards meme studies:

1. Memetics: the study of the cultural evolutionary aspect of memes, the ‘hard science’ of memes

2. Memeology: the study of memecultural social practices, the ‘soft science’ of memes

3. Memeography: the study of memetic artifacts and their environments, the ‘information science’ of memes

Together, these traditions constitute the makings of meme studies (an additional tradition may be worth considering, namely ‘memetic engineering’, which would include the applied science aspects of meme studies), and their epistemologies need not converge any more than the epistemologies of geneticists and ecologists must converge in order for each discipline to constitute part of the broader umbrella of biology. This triad can be understood in analogy with the relatively new field of ecological evolutionary developmental biology (known as eco-evo-devo), an extension resulting from the integration of ecology with another integrated field, evolutionary developmental biology (known as evo-devo). The triad of memetics, memeology, and memeography is analogous to the triad of evolution, development, and ecology, and to the triad of genes, organisms, and environment. Just as eco-evo-devo seeks to understand the interactions between the organism’s genes, development, and environment (Abouheif et al., 2014), so too should meme studies seek to integrate its traditions and understand the interactions between memes, memetic artifacts, users, and their social and technological environments. According to the triadic niche construction theory of hominid evolution, humans developed niches within ecological, neural, and cognitive domains in a way that mutually accelerated their evolution (Iriki & Taoka, 2012). Likewise, the three traditions of meme studies should be integrated in order to promote a mutually accelerated evolution of each. Following the tradition of ‘using memetics to grow memetics’ (Dirlam, 2005), we can use these triadic analogies to further construct our understanding of the meme studies transdiscipline.

Similar subdisciplinary triads exist for other transdisciplines, such as the one within the study of games, which consists of game design, the philosophy of games, and game studies (the narrow academic discipline). While distinct, these subdisciplines need not be segregated. They are mutually supportive and partially overlapping, thereby belonging to a fuzzy set, enriching and expanding the concept of games together. Needless to say, the definition of ‘game’ within game studies is no less contentious than is the definition of ‘meme’ within meme studies. Within game studies, video games and metagames are distinct but inexorably linked objects of research; video games are often also metagames, games about games. The study of video games and metagaming practices each contribute to a deeper understanding of games. The study of memetic artifacts (namely, internet memes) and metamemetic concepts and frameworks (such as meme magic) can and should likewise mediate the study of those objects referred to as memes within the distinct traditions of meme studies.

The source of the deadlock that Tuters seeks a way out of is genic reductionism. It gives rise to the inherent paradox of contemporary memetics. Memetics developed out of a highly specific debate about the units of natural selection during the 70s when reductionism was a much stronger trend, and became an increasingly outdated bridge between the sciences and the humanities. While reductionism has scarcely been ‘supplanted’ in evolutionary biology as Tuters suggests, a ‘vague sense of dissatisfaction permeates the field despite recent developments in both phenotypic and molecular evolution… curious mixing of gene level and phenotypic level views [abound]’ (Schlichting & Pigliucci, 1998, pg. 22). The hope of reductionists to reduce Mendelian theory to molecular genetics, distinct from reducing biological ‘stuff’ metaphysically, has been unsuccessful (Bouchard, 2007, pg. 65). The demand for a replacement for gene-centrism is abundant, as is the supply of replacement candidates, and this has been so for quite some time. But because most meme researchers had an outdated view of foreign disciplines (generally little better than the popular scientific understanding), they each failed to notice just what parts of this bridge were outdated, except where it concerned their home discipline.

It’s not only the new media studies scholars who see memes as a tantalizing conundrum, an apparent fixer-upper that needs a few modifications or concessions before it can be used to operationalize the meme. For instance, computer scientists researching memetic algorithms consider memes a cultural concept first and foremost, not a biological or computer scientific one. They therefore consider memetic algorithms to be inspired by how culture behaves (Moscato, 1989, pg. 29). More interesting still, memetic algorithms are a variant of genetic algorithms, which are algorithms inspired by attempts to emulate biological evolution. Despite Edmonds’ dismissive attitude towards memetic algorithms expressed in his declaration of defeat (Edmonds, 2005), memetic algorithms are not only highly relevant to memetics but also represent one of the two most successful cases of meme studies to date, the other being the study of internet memes. They are particularly interesting as they retain a classical memetic understanding of memes, adapted to the purposes of simulations and algorithms. Moscato first introduced the concept of memetic algorithms by characterizing it as an expansion of his algorithms beyond genetic representations:

I am not constraining a MA [Memetic Algorithm] to a genetic representation… Dawkins says “I am an enthusiastic Darwinian, but I think Darwinism is too big a theory to be confined to the narrow context of the gene.” I have the same impression regarding GA [Genetic Algorithm] or MA to be confined to only genetic representations.

— Moscato, 1989, pg. 29.

On the other hand, machine learning research about memes qua internet memes tends to take the concept entirely for granted: after all, the point is to enable computers to learn and perform without explicit rules and definitions. Hence, Meta’s ‘Hateful Meme Challenge’ paper does not even define ‘meme’, even as it dedicates a section to defining ‘hatefulness’ (Kiela et al., 2020). Whether the exact underlying ontology is deferred to foreign fields or popular understanding, the pattern is roughly that ‘meme’ acts as a shorthand for some entity presumed to be worked out elsewhere by experts. It functions as a means to export some external database of knowledge, which in turn readily interfaces with the discipline into which it is imported. The meme is evidently effective as a conceptual stand-in, allowing researchers to carry out research about ‘memes’ without having to develop entirely new expertise.

Memetics is a science of the artificial modeled after a natural science. It is equal parts grounded in the force of its conceptual scheme and in the hope that a unity of all sciences is possible. This hope of scientific unity has a long history in biology. Its contemporary form has its roots in Julian Huxley’s popular account of biology as a purified, unified, and liberal progressive science. His positivist and liberal view of biology resonated with the public in the 1950s, before giving way to the Modern Synthesis by the 1980s (Smocovitis, 1997, pg. 139). Biology after Darwin is unique among the sciences which branched off from philosophy (such as physics or mathematics) in that it does not leave fundamental questions in the form of ‘what is a number?’ or ‘what is time?’ primarily to the philosophers (Rosenberg, 2016). Yet,

the natural sciences are concerned with the structure and behaviour of things as they are, whereas the artificial sciences must necessarily describe objects from the perspective of what purposes they are or were intended to serve – that is, in the context of how things ought to be.

— Herbert A. Simon, quoted in Dasgupta, 1994, pg. 7.

Memetics occupies the peculiar position of being a science of the artificial modeled after a natural science which was already concerned with prescriptive questions of artificiality (such as selective breeding) and fundamental questions (such as ‘what is a gene?’). Indeed, the very concept of the meme was developed in order to help define the gene (Her, 2018).

Meme studies, also a science of the artificial, must consider not only what meme studies ought to be, but also what the popular and extradisciplinary understanding of meme studies ought to be, and ultimately what memes ought to become. This is precisely what many meme scholars have been doing, leveraging an understanding of data and platforms to facilitate a more holistic theory of memetic evolution. Rogers & Giorgi, taking collections of memes rather than individual memetic artifacts as the unit of analysis, emphasize the ‘specificity of the collection resulting from a database, templating, infrastructural linking, image thread, or search logic’ (Rodgers & Giorgi, 2023). Hagen suggests using ‘meme tracing’ techniques to gather instances of collective self-reference in subcultural spaces into collections called ‘panoramic memes’ (Hagen, 2022). These approaches emphasize the historical, infrastructural, and cultural contexts surrounding memetic artifacts to understand memes as always-already ‘polysemous’ (Boxman-Shabtai & Shifman, 2014; Katz & Shifman, 2017). They square firmly with ecologically and developmentally informed views of evolution such as Developmental Systems Theory (and the analogy between polysemy and gene-environment interaction is a rich one). Furthermore, concepts (such as ‘meme’) are themselves polysemous and elude homogeneous definition (Gerring & Barresi, 2003). The development of multiple definitions and conceptions of the meme is not a weakness but an advantage: it facilitates both the understanding and evolution of new, previously unimagined memes.

The benefits of retaining, modifying, and extending the meme concept are great: the meme is a highly evocative and widely known concept, which many academic researchers have found useful; it provides researchers with countless channels to interface with meme studies (and thereby contribute to its development). Cultural evolution is a promising approach to understanding culture, and memes present a good point of introduction; and the fact that the concept is also widespread in popular culture means that cultural productions are often informed by a notion that culture is memetic, which can act as a self-fulfilling prophecy (which makes the cultural productions indeed memetic and, therefore, perfectly sensible to identify and study as memes).

The primary value of memetics comes from its strategy of applying an evolutionary metaphysics to cultural contexts (Boyd & Richerson, 2000). Meme studies should be an extension of this approach, in the same sense that the Extended Evolutionary Synthesis attempts to be an extension of the Modern Synthesis (Lewens, 2019). Like the proponents of EES, meme studies also faces the triadic task of answering empirical, historical, and conceptual questions regarding the status of meme research. There is a vast amount of such work that can be done under the umbrella of meme studies. The scope of memetic entities should be continually expanded, alongside improved transdisciplinary interchange with other disciplines. For instance, Zulli & Zulli suggest we extend the internet meme concept by including TikTok videos, citing both Dawkins and Shifman along the way (Zulli & Zulli, 2022). While the history of meme studies has been characterized by a radical shrinkage of scope (in response to the failure of Dawkinsianism), it is nevertheless followed by the current gradual expansion of scope. The horizon of meme studies should stretch far beyond a gene-meme analogy or even an analogy between culture and biology. It should aim at an understanding of culture and biology as continuous, revivifying the insight that culture is continuous with biological systems, which made sociobiology and classical memetics so promising. Ultimately, advances made within meme studies should contribute back to evolutionary biology, continuous as they are in their metaphysics.

So, while Dawkinsianism won’t do, the meme concept is worth keeping. But if Dawkins is wrong about both cultural and biological evolution in important ways, what analogy between genes and memes is there to be retained? One answer is that Dawkins’ thesis that cultural evolution is analogous to biological evolution is correct, as well as his secondary thesis that some aspects of cultural evolution are analogous to genic evolution. But because Dawkins’ gene-centrism is rejected, a cultural evolutionary view involving memes need not be meme-centric, nor involve memetic determinism. The persistent failure of memetics parallels similar failures within the modern synthetic paradigm, many of which have been remedied through the advent of the extended synthetic paradigm. Genes exist, even if Dawkinsian genes do not; memes exist, even if Dawkinsian memes do not. In this way, the meme concept, as well as the concept of meme studies, are opened up to new modes of conceptual engineering which enable new interfaces between meme studies and other disciplines.

The benefit of ‘blurring the lines’ (Shifman, 2015) once again, between not just memes and virality but the various understandings of meme studies, is that each one of them, even the popular form, has advantages and unique insights to offer which the others do not. The indeterminacy of the meme concept, like the gene concept, is also its advantage, enabling a plurality of research programs to operate together, at times cooperating and, at others, competing (also like the development of the gene concept). Where reductionism is anathema to many within the humanities, essentialism is similarly unpopular within evolutionary biology, because it is a principal tenet that life evolves. An alternative to either reductionism or essentialism is an ‘integrative pluralism’, as opposed to unification (Mitchell, 2003). A chief aim of meme studies should be the integration of the various disjointed branches of memetics, memeology, memeography, memetic engineering, and folkmemetics through the use of internet memes as model organisms, which in data-centric biology provide ‘reference points’ for just this task (Leonelli, 2016, pg. 145).

The term ‘meme studies’, as opposed to ‘memetics’ or ‘memeology’, is classic transdisciplinary phrasing: whereas multidisciplinarity is an additive gathering of knowledge from multiple disciplines, and interdisciplinarity coordinates the constituent disciplines by emphasizing common ground, transdisciplinarity involves breaking down disciplinary boundaries (Respectively, the metaphors of an encyclopaedia, a bridge, and a jigsaw puzzle seem appropriate. See: Alvargonzález, 2011). The phrasing is reflective of the theoretical strategy typically employed by transdisciplines, which is to designate some abstraction or phenomenon as the object of study, around which a new (trans)disciplinary worldview may crystalize, whilst at the same time helping to conceptually legitimize the object itself. Examples include game studies, comics studies, and area studies (such as Korean studies). Interdisciplines, such as biogeography, cognitive science, sociolinguistics, digital humanities, and medical anthropology, generally involve established disciplines with sophisticated metaphysics and ontologies of their own; the assumption is that the constituent disciplines can readily be made interoperable, and that the synthesis of their respective specialties can yield valuable new knowledge. Multidisciplines, such as health sciences, forensic science, international relations, and environmental science are sprawling and institutionally segmented, without the same aspirations towards epistemologically unifying their member disciplines. While classical memetics aspired towards interdisciplinarity (primarily by subsuming social sciences under evolutionary biology) and memeology largely remained a multidiscipline, meme studies has the makings of a transdiscipline: the pivotal strategic difference for meme studies is that it defers to particular objects in the world (namely, internet memes) in making various decisions about its methodology and metaphysics.

Defining the meme has long remained the holy grail of classical memetics. This is because memes are cultural analogues of genes, and the reductionist approach to biology yielded the tremendous success that is molecular genetics, which memeticists sought to emulate. Classical memeticists hoped that, by precisely defining and identifying the meme, memetics could reach the status of science proper in the way that genetics had done.

Although attempts at defining the internet meme are sometimes still made in earnest, it is rarely the primary concern. Much more typically, Dawkins (1976)or Shifman (2013) are perfunctorily invoked before the paper moves onto more exciting matters than ontology. This pragmatic approach, which enables prioritizing crude empirical research above philosophical debates (recommended to memeticists by David Hull at the 1999 memetics conference. See: Hull, 2000), has proven highly successful for meme studies. But interdisciplinary intellectual debt is created by this strategic deference to designated experts in some field beyond the scope of a particular work. This debt accrues interest in the form of foundational vulnerabilities.

In computer programming, complex software often makes use of preexisting libraries of code written and maintained independently by other people. Such code, referenced from within the codebase but maintained outside of it, is a dependency. Issues downstream can quickly compound if dependencies are not kept updated, because any bugs or security issues are inherited. Much the same is true for transdisciplinary theories such as meme studies: issues compound not only as intellectual debt, but also through the proliferation of work built atop outdated information. For instance, consider a contemporary sociological researcher who disagrees with Dawkins’ views on cultural evolution. Dawkins may know a lot about evolutionary biology, but (the sociologist thinks) he doesn’t know much about culture and sociology. The sociologist cites Dawkins’ 1976 description of how culture might evolve memetically, in order to disagree that culture is analogous to biology. Unless another evolutionary biologist or a philosopher of biology is cited (those cited by Dawkins notwithstanding), the evolutionary biology imported by the sociologist will be a Dawkinsian one. Hence, even as the sociologist might subsequently redefine the meme in sharp contrast against the gene and the meme-as-gene-analogue, that negative redefinition will be shaped by a distinctly opinionated perspective on evolution as a whole.

The impact of extradisciplinary deference is further compounded for interdisciplines: some researchers hailing from disciplines which are neither part of the life sciences nor the cultural studies often defer to Dawkins not only as an expert of evolutionary biology, but also as a cultural scientist. For instance, many machine learning papers cite Dawkins as theoretical fodder to operationalize internet memes, adopting the Dawkinsian gene-culture analogy at face value by taking both his characterization of evolution and culture for granted. Hence, the window of interdisciplinary interfacing becomes fixed here, and is reaffirmed through a chain of intra-disciplinary discourse which constantly refers back to this particular source for definitional, ontological purposes.

The issue of extradisciplinary deference is exacerbated in cases where some secondary work becomes the preferred liaison from the home discipline, adding yet another layer of abstraction (on top of the already narrowed view of the other discipline). Limor Shifman makes just such a move, primarily in her attempt at reining in the gene and returning individual persons as the ‘boss’(Shifman, 2013, pg. 365) of the cultural evolutionary process. Citing Rosaria Conte (Conte, 2000), Shifman calls for memeticists to ‘treat people not as vectors of cultural transmission, but as actors behind this process’(Shifman, 2013, pg. 366). In a later paper written with Segev, Nissenbaum, and Stolero, Shifman endorses a view of memes based on quiddities, which are defined as ‘recurring features that are unique to each family and constitute its singular essence’ (Segev et al., 2015). Together, these positions comprise a return to the pre-Dawkinsian orthodoxy in viewing natural selection as differentially selecting between organisms rather than genes (Sterelny & Kitcher, 1988), as well as to an essentialist, morphological typology of life.

Prima facie, this is a non-issue: memes are not biological organisms, nor intended to be simulations of life. But the received view of memetics from Shifman, in swapping out aspects of Dawkins’ gene-centrism for parts more palatable to communications scholars, ends up blockading the path to keeping the inner workings of meme theory up to date (a task traditionally handled by philosophers of biology and cultural evolutionary theorists). Furthermore, it isolates meme studies from interfacing with a broader range of disciplines, such as computer science. While the move minimizes ‘discipline conflicts’ (Choi & Pak, 2007), it is a strategic mistake that forfeits the potential of meme studies as an inclusive transdiscipline. Nor does an agent-centric view of cultural evolution automatically achieve the aims of giving individuals their due as beings with free will and agency. According to Levins and Lewontin:

Classical Darwinism places the organism at the nexus of internal and external forces, each of which has its own laws, independent of each other and of the organism that is their creation. In a curious way the organism, the object of these forces, becomes irrelevant for the evolutionist, because the evolution of organisms is only a transformation of the evolution of the environment.

— Levins & Lewontin, 1985, pg. 88.

The situation for meme studies resembles the major transition in evolutionary biology, which became possible thanks to technological advancements such as ecological simulation and computational genomic methods. But even more, the situation is similar to the one once faced by game studies. While game studies, the study of ‘not one medium, but many different media’, successfully defended against ‘colonizing attempts from [cinema, literature, and new media studies]’ (Aarseth, 2001), ‘it certainly never was, and never will be, a discipline or -ology, a coherent domain defined by a single set of methods, empirical objects, and research questions and motivations’ (Aarseth, 2015). Like the ‘blurry boundaries’ Shifman praises between memeology and virality studies (Shifman, 2015), Aarseth is content to leave game studies as ‘a fuzzy set, equally hard to define as its mother object, games’ (Aarseth, 2015). Games, the paradigmatic example of Wittgensteinian family resemblance, may be operationalized as fuzzy sets (Veri, 2023). It is possible that game studies, and additionally memes and meme studies, may also be conceptualized along these lines, in the same way that Pigliucci suggests Wittgensteinian family resemblance as a solution for the species problem (Pigliucci, 2003).

Deterding, however, finds in his scientometric analysis of game research that game studies has attained but a ‘Pyrrhic Victory’, consisting of ‘homogenous epistemic cultures [that] retain internal rifts between humanities and social sciences’ (Deterding, 2017). This Pyrrhic victory can be avoided by meme studies through the reintegration of its traditions around a metascientific core. This reintegration involves embracing memetics, memeology, memeography, folkmemetics, and other approaches to meme studies as part of a fuzzy set, while at the same time resisting the epistemic homogenisation of meme studies (whether along the sociobiological line of memetics or the humanities line of memeology). To secure a reliable metascientific core for meme studies, meme studies researchers should favor an intradisciplinary deference to primary research on internet memes, and develop tools, infrastructures, standards, and networks for the sharing of data and resources. They should also reject extradisciplinary deference that substitutes for engagement with unfamiliar disciplines and methodologies, which inevitably tends towards insularity. Nowhere is the value of such transdisciplinary inclusivity more apparent than in the influences for Shifman’s own work. Although Shifman misinterprets Conte as advocating for the role of ‘human agents’, Conte’s original article (which was ‘most important’ to Shifman’s 2013 article. See: Shifman, 2013, pg. 366) is focused on agents in the sense of being ‘limited autonomous agents’, as components in a model of social environments such as intelligent software agents, Multi-Agent Systems and Artificial Societies (Conte, 2000). The internet provides an increasingly, overwhelmingly rich interface through which a portion of each agent within its system may be observed and understood. Not only is there selection and evolution among memes, there is also selection and evolution amongst the agents themselves, modulated and amplified through the design of online platforms which act as the great ecosystems of memes, which themselves are constantly being (niche) constructed.

As Conte emphasizes, decision-making agents that select for memes are essential for modeling cultural evolution (Conte, 2000). Although model agents that simulate cultural evolution do not have the type of agency which Shifman mistakes Conte as advocating for, the point of reference in models must ultimately be the phenomena being modeled (namely, social environments). Ultimately, the data collected by meme scholars (whether from memes found in the wild or simulated in the lab) should be the principal focus that unites the discipline and facilitates collaboration, as Leonelli outlines in the context of biology (Leonelli, 2016, pg. 145). Leonelli redefines (research) data as ‘any product of research activities, ranging from artifacts such as photographs to symbols such as letters or numbers, that is collected, stored, and disseminated in order to be used as evidence for knowledge claims’ (Leonelli, 2016, pg. 77).

The internet and memetics are a ‘match made in heaven’ as Shifman suggests (Shifman, 2013, pg. 365). This is true not only because memes are abundant online, but because the digital environment enables a detailed study of memetic data in a way that has never before been available. Data online can be readily captured with much higher fidelity than with real life social environments, and we may even ‘consider Twitter and memes as the drosophila of our social sciences, which will help decode the elementary processes of replications’ (Boullier, 2018). However, it must be made clear that the usage of internet memes as model organisms does not mean that internet memes are the paradigm cases of memes. Drosophila melanogaster were instrumental in the success of Mendelism not because they were exemplary organisms, but because they breed quickly and have just four pairs of extremely large chromosomes in their salivary glands. Internet memes are likewise expedient, but will not be unproblematically representative of memes in an expansive sense (Ankeny & Leonelli, 2021).

Peeters et al. (2021) present an exemplar of a data centric meme studies that is much more Contean than Shifman’s own. Using historical data of 4chan /pol/ and Encyclopaedia Dramatica, Peeters et al. conduct a corpus linguistic analysis and discover Deleuzian-Austinian (as opposed to Wittgensteinian) ‘language games’ that develop stigmergically. However, they reject the cultural evolutionary framework on the grounds that memetics (here, Peeters et al. use memetics to stand in for Darwinian theories of culture generally) ‘lacks an account of the role of media environments in co-shaping the evolution of ideas’ and is ‘medium insensitive’. However, medium insensitivity is a useful trait for a theory, enabling ‘substrate neutral’ (Her, 2018) explanations that are not restricted to, say, insects in the case of stigmergy.

Peters et al.’s dismissal of Darwinian cultural evolutionary theory is partly based on a misguided book by Tony D. Sampson (Sampson, 2012), and falls into the trap of extradisciplinary deference. ‘In memetics, the medium in which an idea is transmitted is typically dismissed as an inert channels through which the determining fitness algorithm is transmitted… Memetics is a theory that ultimately argues that the illusion of conscious freewill is attributable to a code’, claims Sampson. According to Sampson, Tardean-Deleuzian ‘hypnotic contagions’, as opposed to Darwinian cultural evolution, drive social contagion (Sampson, 2012, pp. 72-78). The criticisms of memetics Sampson discusses in the book are levied not at the then-contemporary literature of the 2010s, but that of the 90s. Furthermore, Sampson’s representatives for the memetics camp (here standing in for neo-Darwinians in general) include contentious popularizers such as Blackmore (The Meme Machine, 1999) and Aaron Lynch (Thought Contagion, 1996) who focused on sensationalist topics such as whether memes preclude free will.

Henrich, Boyd, and Richerson, three major proponents of another medium-sensitive, co-evolutionary, co-shaping view of cultural evolution known as Dual Inheritance Theory, put it thus:

The disputants take the main issue to be whether or not culture is highly analogous to genes. If so, then their evolution is to be explained by Darwinian fitness; if not, Darwinism is useless… The proper approach is to recognize that the analogy between genes and culture is quite loose, and to build up a theory of cultural evolution that takes into account the actual properties of the cultural system.

— Henrich, et al., 2008, pg. 134.

Henrich et al. advocate for a ‘methodological pluralism’ within cultural evolutionary theory, which integrates insights and data from a genuinely diverse set of fields ranging from learning theory and statistical mechanics to game theory and anthropology. Ecological-Economic Processes, one component of the cultural evolutionary program they propose, has become particularly relevant with the advent of economic meme assets (Costola et al., 2021). Even without the cybercultural dimension, economic processes are readily characterized in evolutionary, if not memetic, terms. Schlaile suggests introducing a new program of ‘economemetics’ into the more established field of evolutionary economics by combining memetics and memeology (Schlaile, 2020).

Peeters et al.’s usage of Deleuzian pragmatics is another case of extradisciplinary deference in the same form as Shifman’s extradisciplinary deference to Dawkinsianism. It relies on Austin’s pioneering work (from the 50s/60s) on illocutionary speech acts, through Deleuze and Guattari’s philosophical interpretation of the linguist (from the 80s). Thus, cultural evolution is dismissed on extradisciplinary deferential grounds, based on an outdated interpretation of Neo-Darwinism, and additional extradisciplinary dependencies are introduced to fill the gap, which also turn out to be outdated. The danger of such deference is not only that it introduces dependency issues to the framework (after all, classical memetics already performs this role in frameworks which have not had Dawkins swapped out for Deleuze). It also precludes attempts at updating the dependencies for the most integral components of the interdiscipline. Instead, they are replaced with more familiar intradisciplinary substitutes, whether this be Simondonian coevolution or Deleuzian pragmatics. This tendency to replace one extradisciplinary dependency with another, rather than update it, may be one reason that interdisciplines tend towards a lack of actual interdisciplinarity (Veri, 2023). The problem with meme studies is not that it selected the wrong foundations half a century ago, but rather that it has not properly updated its dependencies. Contrast this with Francico Yus’ work on the cyberpragmatics of Internet memes (Yus, 2023), based on the work of Deidre Wilson and Dan Sperber (Sperber & Wilson, 1995), two anti-Dawkinsian cultural evolutionists. Yus integrates up-to-date frameworks and methodologies from distinct fields such as relevance theory, cyberlinguistics, comics studies, and humor studies, as well as from memetics, memeology, and memeography. The result is an expansive practice of meme studies.

‘Borrowing a term from the fields of contemporary evolutionary theory—as opposed to the out-dated variety of memetics,’ Peeters et al. (2021) apply stigmergy to internet memes. They conceptualize the repurposing of ‘kek’, from a social metagame within World of Warcraft (in which chat from opposing factions were scrambled, turning ‘lol’ into ‘kek’) into a meme-magical extremist trope by /pol/, as an instance of stigmergy. Stigmergy, originating in the 50s as a concept, occupies a similar niche to memetics in that its mainstream usage is limited to swarm intelligence and entomology, but is sometimes utilized in cultural studies for its potency as a metaphor. Despite Peeters et al.’s disavowal of memetics as outdated and Darwinian cultural evolution as ‘medium insensitive’, this usage of stigmergy can be considered an example of the triadic structure of meme studies. Corpus linguistics, stigmergy, and Deleuzian language game theory respectively slot into the triadic scheme of memeography, memetics, and memeology; each component respectively focuses on memetic artifacts, memes, and metamemes. Prior work in the lineage of data-centric meme studies supports this suggestion that this is an example of a modified memetics and memeology. Using data collected from Picbreeder, a collaborative evolutionary art platform, Secretan argues that memetic evolution is often also stigmergic (Secretan, 2013). Heylighen, a major classical memeticist, also suggests that open-source software development involves stigmergy (Heylighen, 2007). Stigmergy and memetics, even in their classical forms, are not mutually exclusive, and instead support the case for methodological pluralism.

Game studies also provides another point of commonality between memes and stigmergic swarms: the Deleuzian language games identified by Peeters et al., in which users game the platform affordances of wikis and imageboards, may be best understood as stigmergically played metagames, like the ‘swarm harassment campaign’ of GamerGate (Her, 2021). Peeters et al. also point out the reflexive performativity of Deleuzian language games. Not only are game studies and meme studies both sciences of the artificial, they are also both unusual in their high degrees of reflexivity. The production of memes is open almost by definition, and many meme researchers also produce memes and run memepages; some memecultures are also academic in nature, and some are even about meme studies. Likewise, gamers and game developers also often consume games about games and game studies literature, whether indirectly through reviews or video essays, or directly through reading papers and watching talks. This reflexivity is not merely a matter of bilateral influence but an ecological integration. Game studies scholars are engaged in games and metagames as part of their research practices and in the metagames of academia; meme studies scholars generate, evolve, and pass on memes about memes through their research. Additionally, games are a frequent source of memes, and memes increasingly feature in games; metagames such as those within streamer culture constitute both games (which are also metamemes) and memes (which are also metagames) (Rudenshiold, 2022; Her, 2022). This points to the fact that games may be understood memetically and memes may be understood ludically.

A significant portion of the reflexive performativity which Peeters et al. find within the language game of /pol/ concerns the rise of meme magical concepts during 2016-2018:

While it would be misleading to say that the users of these terms actually believe in the power ironically ascribed to these practices, the simple act of signification represented by giving these things a name positions them as performative artefacts around which the subculture imagines itself in a self-reflexive manner.

— Peeters et al., 2021, pg. 11

In a theoretical move that is useful for understanding this situation, Lankshear makes the point that a ‘post-knowledge epistemology’ operates within postmodernity: exchange of data seems to have become a sufficient condition for information, and such information may be used and acted upon without any belief or understanding (Lankshear, 2003). Tuters’ point that ‘meme magic is real but memes are not’ (Tuters, 2021) fits seamlessly into both Lankshear’s post-knowledge epistemological framework and Peeters et al.’s framework of Deleuzian language games. Users involved in memetic subcultures behave ‘as though they were possessed of their own agency–into the flow of which speakers then find themselves immersed… whether people are serious in their views, the fact is that they make memes real by using them.’ (Tuters, 2021) Tuters’ description of how memes are made real applies as much to memes as to games, whether they be video games, language games, metagames, or diagram games (Her, 2017).

As demonstrated by the natural fit of the Deleuzian language games frame in the analysis of memes, hybridization between game studies and meme studies is likely to be fruitful. According to Conte, hybridization across social and evolutionary simulation research provides new opportunities for memetics: ‘memetic phenomena can be observed in artificial societies with learning and evolutionary agents, as well as with intelligent agents… learning and intelligent agents will merge into a greater extent than has been the case so far’ (Conte, 2000).

Conte’s expansive vision was substantively realized in the new discipline of computational social science, outlined in the Manifesto of Computational Social Science as ‘a truly interdisciplinary approach, where social and behavioral scientists, cognitive scientists, agent theorists, computer scientists, mathematicians and physicists cooperate side-by-side to come up with innovative and theory-grounded models of the target phenomena’ (Conte, 2012). The memetic component has yet to be integrated. Revisiting computational and biological thinking may prove useful in the process of further hybridization, and provide new ways for disciplines to interface with meme studies.

Another promising point of interface for meme studies is with artificial intelligence and machine learning. Applying a memetic frame to machine learning, and analogizing between machine learning, meme studies, game studies, and biology, also helps to identify the components for an expansive meme concept. Machine learning models harbor latent spaces, a mathematical space in which representations of data exist closer or further apart depending on their respective similarity at many dimensions. The clusters of concepts within latent spaces may be loosely conceptualized as memes, and the latent spaces themselves as a reified form of evolutionary landscapes (they are of course different from the evolutionary environment itself, which encompasses the selective pressures exerted on the model). So understood, latent spaces expose memes (as gene analogues) which hitherto lacked memetic artifacts (as organism analogues), to scrutiny: artificial intelligence enables a way to study memes (analogous to studying DNA or the video game code) before their corresponding memetic artifacts (analogous to organisms or video games) exist in the first place. One example is the use of prompt engineering to excavate folkbiological concepts embedded in art history (Her, 2023). Such memeculturally informed folkbiology provides yet another interface with biology as well as with classical memetics, namely the study of animal culture such as birdsongs (pioneered by Alejandro Lynch, not to be confused with Aaron Lynch) (Sebastián-González & Hart, 2017). Of course, items within latent spaces are not memes in themselves any more than DNA strands are genes in themselves or video game code is games in themselves. Rather, they are data about memes in themselves.

Each of these artifacts facilitates processes and embodies abstractions. There is always ‘a meta-level of activity’ around such artifacts, which Evnine (Evnine, 2018) refers (in the memetic context) to as memographic practices, analogous to metagames (Boluk & Lemieux, 2018) or the environment. According to Evnine, memes are ‘abstract artefacts’ and ‘sets of norms for the production of things (images, actions, tweets, book titles, etc.) and users produce instances of these memes by following the norms in the set’, and not the instances of those norms or the contents of those sets (Vulliamy, 2021; Evnine, 2021). The equivalent view (that games are their rulesets) is common enough within game studies that Boluk and LeMieux go so far as to argue that ‘videogames aren’t games—they’re tools, toys, instruments, equipment, mechanisms, and media for making metagames’ (Boluk & Lemieux, 2018), though elsewhere they endorse what Evnine calls ‘a benign ambiguity’ regarding the use of ‘meme’ to refer both to memetic artifacts and their attendant norms, proposing that some video games are also games and metagames (Boluk & Lemieux, 2017).

According to Developmental Systems Theory (DST), the unit of evolution is not the gene, but the whole system including the gene, the organism, and the environment. Adapting DST to memes and creating a Memetic Systems Theory (Her, 2018), we can define memes as the whole system consisting of the memetic artifacts, memetic norms, and the memetic environment. The memetic environment would include everything from social media platforms to users, and the affordances of the platforms and the psychology and behavior of the users would be as essential to the analysis. This expansion of the meme concept enables access to new data, just as Peeters, et al.’s corpus linguistic research reveals patterns that may otherwise have not been accessible. Even more importantly, it allows the integration and exchange of data across the disparate traditions within meme studies, allowing data to travel in the Leonellian sense (Leonelli, 2016).

More than benign, the polysemy of the meme is what enables its expansiveness. This expansive meme concept should integrate memetic, memeological, and memeographic modalities without having one subsume another. For this, we need a philosophy of memes that can replace Dawkinsianism without a regress into an essentialist and pre-Darwinian understanding of memes and cultural evolution. Additionally, it should wholly embrace the synthetic nature of memes and meme studies: more than any other discipline, even more than game studies (which creates its own games even as it analyses games) or metaphilosophy (which creates new philosophies through the study of philosophy), meme studies is engaged in the construction of cognitive ecosystems even as it studies them. Metamemetics is both the study of meme studies as well as the study of memes, albeit a very specific kind. Just as a post-knowledge epistemological engagement with meme magic makes it real (as real as any metagame), meme studies as a transdiscipline will be one which can direct its own evolution. New philosophies (and new memes) of meme studies should be continually developed in order to support this evolution. Let’s make meaningful memes, because meme studies will be what we make it.

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