Replicated Typo

CogSci 2013 – the others

It’s over but there’s loads of cool papers I didn’t cover. Below is probably not a definitive list because there are SO MANY papers here, but here’s a good flavour of of the more language evolutiony offerings. In no particular order.

Language and Gesture Evolution by Call, Goldin-Meadows, Hobaiter, Liebal and Tomasello

Abstract:

In humans, gestural communication is closely intertwined with language: adults perform a variety of manual gestures, head movements and body postures while they are talking, children use gestures before they start to speak, and highly conventionalized sign systems can even replace spoken language. Because of this role of gestures for human com-munication, theories of language evolution often propose a gestural origin of language. In searching for the evolutionary roots of language, a comparative approach is often used to investigate whether any precursors to human language are also present in our closest relatives, the great apes, because of our shared phylogenetic history. Therefore, the aim of this symposium is to present recent progress in the field of language evolution from both a developmental and compa-rative perspective and to discuss the question if and to what extent a comparison with nonhuman primates is suitable to shed light on possible scenarios of language evolution.

Individuals recapitulate the proposed evolutionary development of spatial lexicons by Carstensen and Regier

Abstract:

When English speakers successively pile-sort colors, their sorting recapitulates an independently proposed hierarchy of color category evolution during language change (Boster, 1986). Here we extend that finding to the semantic domain of spatial relations. Levinson et al. (2003) have proposed a hierarchy of spatial category evolution, and we show that English speakers successively pile-sort spatial scenes in a manner that recapitulates that proposed evolutionary hierarchy. Thus, in the spatial domain, as in color, proposed universal patterns of language change based on cross-language observations appear to reflect general cognitive forces that are available in the minds of speakers of a single language.

Systems from Sequences: an Iterated Learning Account of the Emergence of Systematic Structure in a Non-Linguistic Task by Cornish, Smith and Kirby

Abstract:

Systematicity is a basic property of language and other culturally transmitted behaviours. Utilising a novel experimental task consisting of initially independent sequence learning trials, we demonstrate that systematicity can unfold gradually via the process of cultural transmission.

Experimental insights on the origin of combinatoriality by Roberts and Galantucci

Abstract:

Combinatoriality—the recombination of a small set of basic forms to create an inﬁnite number of meaningful units—has long been seen as a core design feature of language, but its origins remain uncertain. Two hypotheses have been suggested. The ﬁrst is that combinatoriality is a necessary solution to the problem of conveying a large number of meanings; the second is that it arises as a consequence of conventionalisation. We tested these hypotheses in an experimental-semiotics study. Our results supported the hypothesis based on conventionalisation but offered little support for the hypothesis based on the number of meanings.

Combinatorial structure and iconicity in artificial whistled languages by Verhoef, Kirby and de Boer

Abstract:

This article reports on an experiment in which artificial languages with whistle words for novel objects are culturally transmitted in the laboratory. The aim of this study is to investigate the origins and evolution of combinatorial structure in speech. Participants learned the whistled language and reproduced the sounds with the use of a slide whistle. Their reproductions were used as input for the next participant. Cultural transmission caused the whistled systems to become more learnable and more structured. In addition, two conditions were studied: one in which the use of iconic form-meaning mappings was possible and one in which the use of iconic map- pings was experimentally made impossible, so that we could investigate the influence of iconicity on the emergence of structure.

Linguistic structure is an evolutionary trade-off between simplicity and
expressivity by Smith, Tamariz and Kirby

Abstract:

Language exhibits structure: a species-unique system for expressing complex meanings using complex forms. We present a review of modelling and experimental literature on the evolution of structure which suggests that structure is a cultural adaptation in response to pressure for expressivity (arising during communication) and compressibility (arising during learning), and test this hypothesis using a new Bayesian iterated learning model. We conclude that linguistic structure can and should be explained as a consequence of cultural evolution in response to these two pressures.

Communicative biases shape structures of newly acquired languages by Fedzechkina, Jaeger and Newport

Abstract:

Languages around the world share a number of commonalities known as language universals. We investigate whether the existence of some recurrent patterns can be explained by the learner’s preference to balance the amount of information provided by the cues to sentence meaning. In an artificial language learning paradigm, we expose learners to two languages with optional case-marking – one with fixed and one with flexible word order. We find that learners of the flexible word order language, where word order is uninformative of sentence meaning, use significantly more case-marking than the learners of the fixed word order language, where case is a redundant cue. The learning outcomes in our experiment parallel a variety of typological phenomena, providing support for the hypothesis that communicative biases can shape language structures.

Regularization behavior in a non-linguistic domain by Ferdinand, Thompson, Kirby and Smith

Abstract:

Language learners tend to regularize unpredictable variation and some claim that is due to a language-specific regularization bias. We investigate the role of task difficulty on regularization behavior in a non-linguistic frequency learning task and show that adults regularize variable input when tracking multiple frequencies concurrently, but reliably reproduce the variation they have observed when tracking one frequency. These results suggest that regularization behavior may be due to domain-general factors, such as memory limitations.

Learning, Feedback and Information in Self-Organizing Communication Systems by Spike, Stadler, Kirby and Smith

Abstract:

Communication systems reliably self-organize in populations of interacting agents under certain conditions. The various fields which model this – game theory, cognitive science and evolutionary linguistics – make different assumptions about the learning and behavioral processes which are responsible. We created an exemplar-based framework to directly compare these approaches by reproducing previously published models. Results show that a number of mechanisms are shared by the systems which can construct optimal communication. Three general factors are then proposed to underlie any self-organizing learned system.

A robustness approach to theory building: A case study of language evolution by Irvine, Roberts and Kirby

Abstract:

Models of cognitive processes often include simplifications, idealisations, and fictionalisations, so how should we learn about cognitive processes from such models? Particularly in cognitive science, when many features of the target system are unknown, it is not always clear which simplifications, idealisations, and so on, are appropriate for a research question, and which are highly misleading. Here we use a case-study from studies of language evolution, and ideas from philosophy of science, to illustrate a robustness approach to learning from models. Robust properties are those that arise across a range of models, simulations and experiments, and can be used to identify key causal structures in the models, and the phenomenon, under investigation. For example, in studies of language evolution, the emergence of compositional structure is a robust property across models, simulations and experiments of cultural transmission, but only under pressures for learnability and expressivity. This arguably illustrates the principles underlying real cases of language evolution. We provide an outline of the robustness approach, including its limitations, and suggest that this methodology can be productively used throughout cognitive science. Perhaps of most importance, it suggests that different modelling frameworks should be used as tools to identify the abstract properties of a system, rather than being definitive expressions of theories.

And last but not least…replicated typo’s very own Sean Roberts with A Bottom-up approach to the cultural evolution of bilingualism

Abstract:

The relationship between individual cognition and cultural phenomena at the society level can be transformed by cultural transmission (Kirby, Dowman, & Griffiths, 2007). Top-down models of this process have typically assumed that individuals only adopt a single linguistic trait. Recent extensions include ‘bilingual’ agents, able to adopt multiple linguistic traits (Burkett & Griffiths, 2010). However, bilingualism is more than variation within an individual: it involves the conditional use of variation with different interlocutors. That is, bilingualism is a property of a population that emerges from use. A bottom-up simulation is presented where learners are sensitive to the identity of other speakers. The simulation reveals that dynamic social structures are a key factor for the evolution of bilingualism in a population, a feature that was abstracted away in the top-down models. Top-down and bottom-up approaches may lead to different answers, but can work together to reveal and explore important features of the cultural transmission process.

Turtles All the Way Down: How Dennett Thinks

An Essay in Cognitive Rhetoric

I want to step back from the main thread of discussion and look at something else: the discussion itself. Or, at any rate, at Dennett’s side of the argument. I’m interested in how he thinks and, by extension, in how conventional meme theorists think.

And so we must ask: Just how does thinking work, anyhow? What is the language of thought? Complicated matters indeed. For better or worse, I’m going to have to make it quick and dirty.

Embodied Cognition

In one approach the mind’s basic idiom is some form of logical calculus, so-called mentalese. While some aspects of thought may be like that, I do not think it is basic. I favor a view called embodied cognition:

Cognition is embodied when it is deeply dependent upon features of the physical body of an agent, that is, when aspects of the agent’s body beyond the brain play a significant causal or physically constitutive role in cognitive processing.

In general, dominant views in the philosophy of mind and cognitive science have considered the body as peripheral to understanding the nature of mind and cognition. Proponents of embodied cognitive science view this as a serious mistake. Sometimes the nature of the dependence of cognition on the body is quite unexpected, and suggests new ways of conceptualizing and exploring the mechanics of cognitive processing.

One aspect of cognition is that we think in image schemas, simple prelinguistic structures of experience. One such image schema is that of a container: Things can be in a container, or outside a container; something can move from one container to another; it is even possible for one container to contain another.

Memes in Containers

The container scheme seems fundamental to Dennett’s thought about cultural evolution. He sees memes as little things that are contained in a larger thing, the brain; and these little things, these memes, move from one brain to another.

This much is evident on the most superficial reading of what he says, e.g. “such classic memes as songs, poems and recipes depended on their winning the competition for residence in human brains” (from New Replicators, The). While the notion of residence may be somewhat metaphorical, the locating of memes IN brains is not; it is literal.

What I’m suggesting is that this containment is more than just a contingent fact about memes. That would suggest that Dennett has, on the one hand, arrived at some concept of memes and, on the other hand, observed that those memes just happen to exist in brains. Yes, somewhere Over There we have this notion of memes as the genetic element of culture; that’s what memes do. But Dennett didn’t first examine cultural process to see how they work. As I will argue below, like Dawkins he adopted the notion by analogy with biology and, along with it, the physical relationship between genes and organisms. The container schema is thus foundational to the meme concept and dictates Dennett’s treatment of examples.

The rather different conception of memes that I have been arguing in these notes is simply unthinkable in those terms. If memes are (culturally active) properties of objects and processes in the external world, then they simply cannot be contained in brains. A thought process based on the container schema cannot deal with memes as I have been conceiving them. Continue reading “Turtles All the Way Down: How Dennett Thinks”

Cultural Evolution, So What?

I’d like this to be the last post in this series except, of course, for an introduction to the whole series, from Dan Dennett on Words in Cultural Evolution on through to this one. We’ll see.

I suppose the title question is a rhetorical one. Of course culture evolves and of course we need to a proper evolutionary theory in order to understand culture. But the existing body of work is not at all definitive.

In the first section of this post I have some remarks on genes and memes, observing that both concepts emerged as place-holders in a larger ongoing argument. The second section jumps right in with the assertion, building on Dawkins, that the study of evolution must start by accounting for stability before it can address evolutionary change. The third and final section takes a quick look at change by looking at two different verstions of “Tutti Frutti”. There’s an appendix with some bonus videos.

From Genes to Memes

I’ve been reading the introduction to Lenny Moss, What Genes Can’t Do (MIT 2003), on Google Books:

The concept of the gene, unlike that of other biochemical entities, did not emerge from the logos of chemistry. Unlike proteins, lipids, and carbohydrates, the gene did not come on the scene as a physical entity at all but rather as a kind of placeholder in biological theory… The concept of the gene began not with the intention to put a name on some piece of matter but rather with the intention of referring to an unknown something, whatever that something might turn out to be, which was deemed to be responsible for the transmission of biological form between generations.

Things changed, of course, in 1953 when Watson and Crick established the DNA molecule and the physical locus of genes.

The concept of the meme originated in a similar way. While the general notion of cultural evolution goes back to the 19th century, it was at best of secondary, if not tertiary, importance in the 1970s when Dawkins write The Selfish Gene. And while others had offered similar notions (e.g. Cloake), for all practical purposes, Dawkins invented the concept behind his neologism, though it didn’t began catching on until several years after he’d published it.

The concept still functions pretty much as a placeholder. People who use it, of course, offer examples of memes and arguments for those examples. But there is no widespread agreement on a substantial definition, one that has been employed in research programs that have increased our understanding of human culture. Continue reading “Cultural Evolution, So What?”

CogSci 2013: Communication Leads to the Emergence of Sub-optimal Category Structures

Next up is Catriona Silvey, Simon Kirby and Kenny Smith, who use an experiment which gets participants to categorise shapes from a continuous space either in a communicative condition or a non-communicative condition. You can read it here (you should, it’s really awesome, and I only describe it briefly below): http://www.lel.ed.ac.uk/~s1024062/silvey_cogsci.pdf

Silvey et al. are interested in how semantic categories emerge. They set up an experiment in which participants were given a continuous semantic space:

In one condition single participants had to simply divide the space up into different labeled categories. In another condition, participants had to play a communication game. Participants communicated in pairs using the same semantic space. In both conditions, participants were given nonsense words to label their categories. Participants could assign as many categories as they liked.

In the communication condition one participant was the sender and one was the receiver. The sender chose a word to communicate a given shape from the grid above, and the receiver had to chose which shape they thought the word referred too. Participants were then given feedback as to whether the receiver had chosen the right image. They were then given a score based on how close the chosen shape was to the original given shape. The sender and received swapped roles every trial. Together they labelled every shape 4 times throughout the experiment and the last label for each shape chosen by both participants were taken for analysis.

An optimal categorisation strategy within this game would be to give every shape its own label, however, memory constraints are likely to stop participants using this strategy. Given that you will score more if shapes are closer, it was expected that participants would use small, clustered and equally sized categories in order to optimise getting the right shape, and if not, maximising their score.

In the non-communicative experiment, participants arranged the categories in fairly balanced chunks that would have served relatively optimally for the communication game. However, despite expectations, participants in the communicative condition behaved sub-optimally and did not maximise their communicative success (their score in the game) in that their categories weren’t clustered or optimal in colour or size. This could have been caused by the communicative condition having extra pressure for the learnability of categories, as well as a pressure for communicative success, which the non-communicative condition did not have. The authors argue that this is possibly a demonstration for how real languages arrive at suboptimal categories, e.g. where words vary as to whether they represent a very small category or represent a much broader part of the semantic space.

The Mind is What the Brain Does, and Very Strange

Having now clearly established memes as properties of objects and events in the external world, properties that provide crucial data for the operation of mental “machines,” I want to step aside from thinking about memes and cultural evolution as such and think a bit about the mind. I want to set this conversation up by, once again, quoting from Dennett’s recent interview, The Well-Tempered Mind, at The Edge:

The question is, what happens to your ideas about computational architecture when you think of individual neurons not as dutiful slaves or as simple machines but as agents that have to be kept in line and that have to be properly rewarded and that can form coalitions and cabals and organizations and alliances? This vision of the brain as a sort of social arena of politically warring forces seems like sort of an amusing fantasy at first, but is now becoming something that I take more and more seriously, and it’s fed by a lot of different currents.

A bit later:

It’s going to be a connectionist network. Although we know many of the talents of connectionist networks, how do you knit them together into one big fabric that can do all the things minds do? Who’s in charge? What kind of control system? Control is the real key, and you begin to realize that control in brains is very different from control in computers. Control in your commercial computer is very much a carefully designed top-down thing.

That’s the problem David Hays and I set ourselves in Principles and Development of Natural Intelligence (Journal of Social and Biological Systems 11, 293 – 322, 1988). While we had something to say about control in our discussion of the modal principle, we addressed the broader question of how to construct a mind from neurons that aren’t simple logical switches.

It is by no means clear to me how Dennett, and others of his mind-set, think about the mind. Yes, it’s computational. I can deal with that. But not, as I’ve said, if it’s taken to mean that the primitive operations of the nervous system are like the operations in digital computers, not if it’s taken to imply that the mind is constituted by ‘programs’ written in the ‘mentalese’ version of Fortran, Lisp, or C++. THAT was never a very plausible idea and the more we’ve come to know about the nervous system, the less plausible it becomes.

The upshot is that we need a much more fluid, a much more dynamic, conception of the mind. In Beethoven’s Anvil I talked of neural weather. Here’s how I set-up that metaphor (pp. 71-72): Continue reading “The Mind is What the Brain Does, and Very Strange”

Dennett’s Preformationist Memetics

In thinking about my previous post I realized that my criticism of Dennett’s meme doctrine–that memes are mental entities that move from brain to brain like software viruses or Java apps–amounts to asserting that he’s a preformationist. What’s that? Here’s what the Wikipedia says:

In the history of biology, preformationism (or preformism) is the idea that organisms develop from miniature versions of themselves.

Instead of assembly from parts, preformationists believe that the form of living things exist, in real terms, prior to their development.

The Wikipedia article comes with this illustration, which is a 1695 drawing of a sperm by Nicolaas Hartsoeker.

There you see it on the left, the little human-form homunculus. And there, on the right, the form gets larger and larger during prenatal development.

How, you might ask, could Dennett possibly be a preformationist? After all, ideas don’t have physical shape? Well, no, I suppose they don’t. Here’s what I have in mind (I’m quoting from the end of my previous post):

While I define the ideotype as the cultural analog of the biological phenotype, the objects and processes that I identify as ideotypes are much like Dennett’s memes. They exist inside people’s head, in their minds, as do Dennettian memes, for the most part. Continue reading “Dennett’s Preformationist Memetics”

Memes as Data: Targets, Couplers, and Designators

FLASH! The active brain-hopping meme is to culture as the preformationist germ seed is to biology. More in a later post.

While these posts have been quite critical of Dennett’s use of the concept of information, that should not be taken to mean that I see no use for such a concept. There is, of course, the technical usage established by Shannon and Weaver, but that is of limited use in these discussions. The challenge is to make use a less specialized, indeed an informal, concept. I intend to do so by identifying memetic information with the formal concept of data, as employed in computer science, and in particular with the concept of a parameter.

The Wikipedia defines parameter in this way:

In computer programming, a parameter is a special kind of variable, used in a subroutine to refer to one of the pieces of data provided as input to the subroutine. These pieces of data are called arguments. An ordered list of parameters is usually included in the definition of a subroutine, so that, each time the subroutine is called, its arguments for that call can be assigned to the corresponding parameters.

Memes are arguments in the sense of that definition. The parameters for which they are values are components of “subroutines” in the mind, where, for the purposes of this discussion, the mind is considered to be a rich and sophisticated computational device whose characteristics are unspecified. Continue reading “Memes as Data: Targets, Couplers, and Designators”

CogSci 2013: The Impact of Communicative Constraints on the Emergence of a Graphical Communication System

The Annual Conference of the Cognitive Science Society is happening next week with quite a but of language evolution stuff going on. On the run up I’ll post a few evolutionary linguisticsy papers which will be presented. If you’re presenting something please feel free to send me it to be covered here or write a guest post and I’ll post it up!

Firstly, Bergmann, Lupyan & Dale are presenting a paper called “The Impact of Communicative Constraints on the Emergence of a Graphical Communication System”. The paper can be seen here: http://www.tillbergmann.com/papers/cogsci_squiggle_bergmann_dale_lupyan.pdf

The authors present an experiment in which participants had to communicate using graphical symbols (called squiggles) of faces. The experiment worked as a communication game but also had generational turnover as in iterated learning experiments. They investigated the effect of different features of the input faces and the effect of changing the comprehension condition and how these affected the structure of the symbols that emerged.

The study used Dale & Lupyan’s (2010) squiggle framework but used human faces as the input. Participants were to “squiggle” the face in just 5 seconds to prevent them from building representations which were too detailed and prevented participants from writing words etc. In the first experiment they found that participants used strategies such as using hair shape/length, face shape and features to differentiate between faces and different strategies were more common in some gender/age categories, e.g. women were more likely to be defined by their hair.

The second experiment was the same as the first one but differed in the “listening” round, where participants were to choose which original face a squiggle represented. In experiment 1, participants had to choose between any two faces, in experiment 2 they were to choose between an “opposite” face. Faces differed in being male or female and young or old. So in experiment 2 young females were always pitted against old males, and old females pitted against young males. This was to see if the environment in interrupting the squiggles effected how they were represented and interrupted. This experiment found that squiggles in experiment 2 had less detail in order to be successful, and the amount of complexity fell over generations. I suppose this is an effect of the differentiating features between faces being more salient in the second experiment where faces always differ in both age and gender. This shows that the context in which communication occurs can shape the structure and complexity of that communication.

The SpecGram Essential Guide to Linguistics

What does a Labio-nasal sound like? What is the laziest language on earth? How can a knowledge of linguistics help make macaroni cheese? What is the tiny phoneme hypothesis? Where can you find a book that synergises all the loose ends of linguistics into a unified, transparent theory? I don’t know. In the meanwhile, try reading the Speculative Grammarian Essential Guide to Linguistics.

Many of you will know and fear the Speculative Grammarian journal, the ultimate Shibboleth in the field of languaging (and if you know what a Shibboleth is, and are proud of it, then this might be for you). Now the best cuttings have been complied into a book which takes you on a quiestionable journey right accross the field from phonetics to sociolinguistics in a quest to make linguistics look as bonkers as a real science like quantum physics.

You’ll learn about the linguistic uncertainty principle (it’s impossible to simultaneously know both the synchronic state of a language and the direction of its drift). You’ll revel in the poetry of Yune O. Hūū, II. You’ll understand exactly which part of ‘no’ you don’t understand. You’ll wonder about granular phonology. In fact, you’ll wonder about a lot of things, like how this got published. It even includes the finding that started the whole spurious correlation saga, the role of the Acacia tree in language evolution.

Complete with a choose-your-own-career-in-linguistics adventure game (German-sign-language-shaped dice not included), this is the ultimate gift for the budding language student, the jaded academic or the holistic forensic linguist. And just in time for Christmas.

You can buy the book at the SpecGram website.

Dubious praise:

“Ever wonder why Vikings torched scriptoria? This kind of thing.”
—E. V. Gordon
“Funnier than any other book I’ve read in the entire 20th Century!”
—Rasmus Rask
“Contains more than 100 basic words.”
—Morris Swadesh
“Same reference as linguistics; different sense.”
—Gottlob Frege
“Most of the changes I would make are, of course, to remove commas.”
—An Anonymous Proofreader
“This book is so chock full of borrowings and analogy that it is utterly unsuited to any sort of scholarly discourse.”
—Neogrammarian Quarterly
“Two uvulas down, way down!”
—Sapir and Bloomfield, At the Bookstore

How Do We Account for the History of the Meme Concept?

First, in asking THAT question I do not intend a bit of cutesy intellectual cleverness: Oh Wow! Let’s get the meme meme to examine it’s own history. My purpose would be just as well served by examining, say, the history of the term “algorithm” or the term “deconstruction,” both originally technical terms that have more or less entered the general realm. I’m looking at the history of the meme concept because I’ve just been reading Jeremy Burman’s most interesting 2012 article, “The misunderstanding of memes” (PDF).

Intentional Change

Second, as far as I can tell, no version of cultural evolution is ready to provide an account of that history that is appreciably better than the one Burman himself supplies, and that account is straight-up intellectual history. In Burman’s account (p. 75) Dawkins introduced the meme concept in 1976

as a metaphor intended to illuminate an evolutionary argument. By the late-1980s, however, we see from its use in major US newspapers that this original meaning had become obscured. The meme became a virus of the mind.

That’s a considerable change in meaning. To account for that change Burman examines several texts in which various people explicate the meme concept and attributes the changes in meaning to their intentions. Thus he says (p. 94):

To be clear: I am not suggesting that the making of the active meme was the result of a misunderstanding. No one individual made a copying mistake; there was no “mutation” following continued replication. Rather, the active meaning came as a result of the idea’s reconstruction: actions taken by individuals working in their own contexts. Thus: what was Dennett’s context?

And later (p. 98):

The brain is active, not the meme. What’s important in this conception is the function of structures, in context, not the structures themselves as innate essences. This even follows from the original argument of 1976: if there is such a thing as a meme, then it cannot exist as a replicator separately from its medium of replication.

Burman’s core argument this is a relatively simple one. Dawkins proposed the meme concept in 1976 in The Selfish Gene, but the concept didn’t take hold in the public mind. That didn’t happen until Douglas Hofsadter and Daniel Dennett recast the concept in their 1982 collection, The Mind’s I. They took a bunch of excerpts from The Selfish Gene, most of them from earlier sections of the book rather than the late chapter on memes, and edited them together and (pp. 81-82)

presented them as a coherent single work. Al- though a footnote at the start of the piece indicates that the text had been excerpted from the original, it doesn’t indicate that the essay had been wholly fabricated from those excerpts; reinvented by pulling text haphazardly, hither and thither, so as to assemble a new narrative from multiple sources.

It’s this re-presentation of the meme concept that began to catch-on with the public. Subsequently a variety of journalist accounts further spread the concept of the meme as a virus of the mind.

Why? On the face of it it would seem that the virus of the mind was a more attractive and intriguing concept whereas Dawkins’ original more metaphorical conception. Just why that should have been the case is beside the point. It was.

All I wish to do in this note is take that observation and push it a bit further. When people read written texts they do so with the word meanings existing in their minds, which aren’t necessarily the meanings that exist in the minds of the authors of those texts. In the case of the meme concept, the people reading The Selfish Gene didn’t even have a pre-existing meaning for the term, as Dawkins introduced and defined it in that book. The same would be true for the people who first encountered the term in The Mind’s I and subsequent journalistic accounts. Continue reading “How Do We Account for the History of the Meme Concept?”