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Report on Cultural Evolution for the National Humanities Center, Revised Edition

Back in 2010 I wrote a piece for the National Humanities Center (USA), Cultural Evolution A Vehicle for Cooperative Interaction Between the Sciences and the Humanities, which is online at their Forum along with comments. I have since revised it to include a section on Jockers, Macroanalysis: Digital Methods in Literary History (2013). You can download the revised version from my SSN page. I’ve placed the added section below.

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A Start: 19th Century Anglophone Literary Culture

Let me set the stage by quoting a passage from the excellent review Tim Lewens (2014) wrote for the Stanford Encyclopedia of Philosophy:

The prima-facie case for cultural evolutionary theories is irresistible. Members of our own species are able to survive and reproduce in part because of habits, know-how and technology that are not only maintained by learning from others, they are initially generated as part of a cumulative project that builds on discoveries made by others. And our own species also contains sub-groups with different habits, know-how and technologies, which are once again generated and maintained through social learning. The question is not so much whether cultural evolution is important, but how theories of cultural evolution should be fashioned, and how they should be related to more traditional understandings of organic evolution.

Building on discoveries made by others, we can see that kind of process in a graphic that Matthew Jockers used late in Macroanalysis: Digital Methods in Literary History (2013), though that’s not what Jockers had in mind in that particular investigation. He was working with a corpus of 3346 Ninetheenth Century novels by American, British, Irish and Scottish authors and was interested in tracking influence among them. It is one thing to track influence among a handful of texts; that is the ordinary business of traditional literary history. You read the texts, look for similar passages and motifs, read correspondence and diaries by the authors, and so forth, and arrive at judgements about how the author of some later text was influenced by authors of earlier texts.

It’s not practical to do that for over 3000 texts, most of which you’ve never read, nor has anyone read them in over 100 years. Jockers was using recently developed techniques for analyzing “big data,” in this case, a pile of 19th Century Anglophone novels. Without going into the details – you can find most of them in Jockers, pp. 156 ff.) – Jockers had the computer ‘measure’ each text on almost 600 different traits and then calculated the pair-wise similarity of all the texts. He then tossed out all values below a certain relatively high threshold and then had the computer create a network visualization of the remaining connections. Each text is represented as a ‘node’ in the network and the similarity between two texts is represented by the ‘edge’ (of link) connecting them. The length of the edge is proportional to the degree of similarity. Jockers then had the computer create a visualization of this network, where each text would be next to similar texts in the resulting image. Here’s that image (Figure 9.3 in the book, p. 165, color version from the web):

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It turns out that the visualization routine laid the graph out more or less in chronological order, going from older to newer, left to right. Note that there was no temporal information in the data from which that graph was derived (pp. 164-65):

The fact that they line up in a chronological manner is incidental, but rather extraordinary. The chronological alignment reveals that thematic and stylistic change does occur over time. The themes that writers employ and the high-frequency function words they use to build the frameworks for their themes are nearly, but not always, tethered in time. At this macro scale, style and theme are observed to evolve chronologically, and most books and authors in this network cluster into communities with their chronological peers. Not every book and not every author is a slave to his or her epoch.

On Jockers’ first sentence, it’s neither incidental nor extraordinary IF an evolutionary process regulates cultural change. For evolution proceeds through “descent with modification,” as Darwin put it, and that goes for cultural as well as biological evolution. If a later individual is modified from its immediate predecessors, it will in fact resemble them a great deal; the modifications do not change the basic character of the descendants.

As his language indicates, Jockers wasn’t looking for THAT result. It surprised him. Though he alludes to cultural evolution here and there in the book, he rejected it as a basic premise of his investigation (pp. 171-172). The evolutionary interpretation is mine, not his.

We must further realize that that interpretation is an assertion about the collective mentality. Jockers wasn’t examining the minds of millions of 19th century readers of English-language novels in Britain and America, but the history of those novels is a function of the tastes and interests of those readers. Those books wouldn’t have been written if publishers didn’t think they could see them to the public. Those tastes changed gradually, with the themes and styles of novels appealing to those tastes changing gradually as well.

The study of cultural evolution is thus the study of collective mentality. We are interested in the collective psyche. How can we think of the collective psyche without falling into hopeless mysticism?

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Reading Macroanalysis: Notes on the Evolution of Nineteenth Century Anglo-American Literary Culture

Matthew L. Jockers. Macroanalysis: Digital Methods & Literary History. University of Illinois Press, 2013. x + 192 pp. ISBN 978-0252-07907-8

I’ve compiled all the posts into a working paper. HERE’s the SSRN link. Abstract and introduction below.

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Abstract: Macroanalysis is a statistical study of a corpus of 3346 19th Century American, British, Irish, and Scottish novels. Jockers investigates metatdata; the stylometrics of authorship, gender, genre, and national origin; themes, using a 500 item topic model; and influence, developing a graph model of the entire corpus in a 578 dimensional feature space. I recast his model in terms of cultural evolution where the dynamics are those of blind variation and selective retention. Texts become phenotypical objects, words become genetic objects, and genres become species-like objects. The genetic elements combine and recombine in authors’ minds but they are substantially blind to audience preferences. Audiences determine whether or not a text remains alive in society.

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Introduction: Get in the Driver’s Seat

I knew it was going to be good. But not THIS good. A better formulation: I didn’t know it would good in THIS way, that it would put me in driver’s seat, if only in a limited way.

The driver’s seat, you ask, what do you mean? In this case it means that I could actively work with the data. When, for example, I read Moretti’s Graphs, Maps, Trees, I read it as I do pretty much any book, though this one had a bunch of charts and diagrams, which is unusual for literary criticism. There wasn’t anything for me to do other than just read.

If I didn’t have ready access to the web, reading Macroanalysis would have been the same. But I do have web access and I use it all the time. So, when I got to Chapter 8, “Theme,” I also accessed the topic browser that Jockers had put on the web. Through this browser I could explore the topic model Jockers used in the book and, in particular, I could use it to investigate matters that Jockers hadn’t considered.

So I moved from thinking about Jockers’ work to using his work for my own intellectual ends. I ended up writing four posts (6.1 – 6.4) on that material totaling almost 12,000 words and I don’t know how many charts and graphs, all of which I got from Jockers’ web site. Once I’d worked through an initial curiosity about a spike that looked like Call of the Wild (but wasn’t, because that text isn’t in the database) I settled into some explorations framed by Leslie Fiedler’s Love and Death in the American Novel, Melville’s Moby Dick, and Edward Said’s anxiety on behalf of the autonomous existence of the aesthetic realm.

Data is Independent of Interpretations

You can do that as well, or whatever you wish. While the web browser gives you only limited access to Jockers’ corpus, that access is real and useful. A lot of work in digital criticism, and digital humanities in general, is like that. It produces ‘knowledge utilities’ that are generally useful, not just the private preserves of the original investigator.

There is an important epistemological point here as well. Jockers was led to this work by a certain set of intellectual concerns. Some of those concerns are quite general–about literature and the novel–while others are more specific–he has a particular interest in Irish and Irish-American literature. But I had no trouble putting his results to use in service of my own somewhat different interests. Continue reading

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From Macroanalysis to Cultural Evolution

The purpose of this post is to recast the work reported in Macroanalysis: Digital Methods & Literary History in terms appropriate to cultural evolution. The idea is to propose a model of cultural evolution and assign objects from Jockerss analysis to play roles in that model. I will leave Jockers’ work untouched. All I’m doing is reframing it.

Before doing that, however, I should note that in the last quarter of a century or so there has been quite a lot of work on cultural evolution in a variety of discipline including linguistics, anthropology, archaeology, and biology. Though it must be done at some time, I have no intention of even attempting to review that work here and so to place the scheme I propose in relation to it. That’s a job for another time and another venue. I note, however, that I have done quite a bit of work on cultural evolution myself and that some of that discussion can be found in documents I list at the end of this post.

Why Evolution?

First of all, why bother to recast the processes of literary history in evolutionary terms at all? Jockers wrote an excellent book without creating an evolutionary model, though he mentioned evolution here and there. What’s to be gained by this recasting?

As far as I can tell, much of the work that has been done on cultural evolution has been undertaken simply to exercise and extend the range of evolutionary discourse. It has not, as yet, resulted in an understanding of cultural process that is deeper than more conventional forms of historical discourse. Much of my own work has been undertaken in this spirit. I believe that, yes, at some point, evolutionary explanation will prove more robust that other forms of explanation, but we’re not there yet.

This work in effect is looking to evolutionary accounts as exhibiting something like formal cause in Aristotle’s sense. Evolutionary accounts are about distribution of traits across populations. In biology such accounts have a characteristic formal appearance so that, e.g. phylogenetic analysis of a population of entities tends to “look” a certain way. So, in the cultural sphere, let’s conduct a similar analysis and see how things look even if we don’t have our entities embedded in the kind of causal framework that genetics and population biology, molecular biology, and developmental biology provide the biologist.

That’s fine, as long as we remind ourselves periodically that that’s what we’re doing. But we must keep looking for the terms in which to construct a causal model.

What I specifically want from an evolutionary approach to culture is

  • a way to think about Said’s autonomous aesthetic realm,
  • a way to prove out Shelley’s assertion that “poets are the unacknowledged legislators of the world,”
  • a way of restoring agency to writers and readers rather than casting them as puppets of various vast and impersonal forces, and
  • a way of thinking about the canon in relation to the whole of literary culture.

That’s what I want. Those requirements imply having a causal model. Whether or not I’ll get it, that’s another matter.

Current critical approaches, however, in which individual humans are but nodal points in the machinations of vast and impersonal hegemonic forces, have trouble on all these points. Individual human beings are deprived of agency thus turning readers into zombies watching the ghosts of dead authors flicker on the remaining walls of Plato’s cave. The canon is captive to those same hegemonic forces, which have promulgated Shelley’s defense as an opiate for the masses, which R’ us.

The critical machine is broken. It’s time to start over. Before we do that, however, I need to dispense with one objection to seeking an evolutionary account of cultural phenomena. Continue reading

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Reading Macroanalysis 6.1: Theme–Dogs, Gold, Slavery, and Awakening

Over at New Savanna I’ve been blogging my way though Matthew Jockers, Macroanalysis: Digital Methods & Literary History, University of Illinois Press, 2013. I figured this particular post would be of interest here. If you’re not familiar wiht topic analysis, there’s some links below that’ll help you out.

Chapter 8 of Macroanalysis is about “Theme.” Jockers uses topic analysis to investigate the occurrence of 500 ‘themes’ in a corpus of 3,346 19th-century British, American, and Irish books. He opens with a bit of intellectual history, from the Russin Formalists to Google’s Ngrams; then he launches into topic analysis, which emerged at the turn of the millennium he gives some simple examples, and then he gets serious. But I’m going to skip over all of that for now.

For one thing, I’ve been through the topic analysis drill several times in the past year or so and don’t want to go through it again. If you need an introduction or a review, check out Topic Models: Strange Objects, New Worlds, or, in this series, Reading Macroanalysis 5: An Interlude on Scale: Micro, Meso, and Macro. For another, Jockers has put a topic tool online, 500 Themes from a corpus of 19th-Century Fiction. Those are the topics he discusses in this chapter.

Once I was done reading the chapter I started playing with the tool. I’d pick a topic and then look at the graphics:

  1. a word cloud to display the most frequent words in the topic,
  2. a bar chart indicating usage of the topic by author gender (male, female, and undetermined),
  3. a line graph showing gender usage over time,
  4. a bar chart indicating usage of topic by author nationality (American, British, Irish).,and
  5. a line graph showing national usage over time.

At first I was just browsing, moving from one theme to the next. But then I hit one that grabbed my attention.

So I spent the next couple of hours looking at themes and thinking about them. I’m going to devote the rest of this post and the next one showing what I found. Then I’ll do a third post where I review what Jockers found and recast the enterprise in terms of cultural evolution.

Note that in all of this I’m just playing around, but in a serious way. It is all preliminary and provisional. I haven’t reached any firm conclusions on the particular themes I look at. The only thing I’m sure about is that this, and similar techniques, are going to revolutionize the way we do literary history.

Before proceeding on, however, two caveats are necessary. While the Jockers’ is substantial it isn’t every British, American, and Irish novel written in the 19th Century. Perhaps more important, it is natural to read these theme charts as reflecting the interests of the 19th Century reading public. And in some sense that is so. But we have to be careful.

For some of these books were more widely read than others and a few of them, the canonical ones, are still being read. But the extent of a books’ readership is not reflected in the data. The fact that a book was published at all implies, of course, that someone thought there was an audience for it. But a publisher’s interest isn’t quite the same as a reader’s interest. We simply don’t know how accurately publisher interest tracks reader interest. With those reservations in mind, let’s take a look.

Of Dogs and Gold

In the course of browsing through Jockers’ themes menu I saw “DOGS.” Let’s look at that, I thought. Why dogs? you may ask. No deep reason, but some years ago, way back in graduate school in fact, I’d noticed that dogs figured as a significant motif in Wuthering Heights. Major transitions among humans were marked by violence between dogs and humans (e.g. Lockwood arrives and is greeted by a barking dog, Catherine gets bitten by Skulker; see this post). More recently, I’d read a handful of articles about the domestication of dogs during human evolutionary history. I was just curious.

Here’s the word cloud for the DOGS topic:

dog cloud

The following graph stunned me. It depicts the occurrence of the dog topic by author’s gender over the course of the century. The medium gray line depicts male authors, the black line females, and the light gray line, authors where the gender was undetermined.

Dogs Gender year

What’s that spike at the right edge? As soon as I realized that it was for male authors I thought, “Jack London, Call of the Wild.” I also had some doubts as to whether that book was in the corpus, as I didn’t believe the book was 19th Century, though I wasn’t sure. But that doubt didn’t stop me from nosing around. By the time I’d confirmed for myself that it wasn’t 19th Century (it was published in 1903) and Jockers had gotten back to me that, no, it wasn’t in the corpus, I’d already had too much fun browsing through the charts and had moved on to other topics (which I’ll get to in the next post). Continue reading

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Functional trade-off between lexical tone and intonation

Languages can use pitch to make lexical contrasts (so called tone languages) or to mark contrasts at the utterance level, usually called intonation, such as using rising pitch to indicate a question as opposed to a statement.  In fact, a language can use pitch to do both by various means such as changes in pitch range.  However, lexical tone and intonation are often seen as mechanisms that compete for pitch resources.  Yip (2002) holds that “it is commonplace that many lexical tone languages avoid the potential conflicts between intonation and lexical tone by using a different mechanism altogether: the sentence-final particle.”

Can we see the evolutionary effects of this dependency in the typology of the world’s languages? (at the very least, the terminology is in competition!  I’ll use ‘intonation’ to mean phrase-level pitch)

Continue reading

PhD positions in the Dynamics of Language

The ARC centre of excellence for the Dynamics of language is offering a number of PhD positions, including on the topic of language evolution.  The positions are hosted at ANU in Canberra, the University of Melbourne and the University of Queensland.  These are on top of the Wellsprings of Diversity positions.

From the website:

The Evolution program will engage with central questions about the evolution of language across scales that range from the whole span of human evolution to the adaptations that occur as speech capacities are lost in speech-impaired individuals. This program will explore what possible structures languages can develop, how learning and processing biases shape the direction of evolution, what is the role of the speech community in language evolution, and how insights from language evolution can help develop more flexible ways of robots learning speech.

Details can be found in the pdfs below.

 

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Review of correlational studies in linguistics

Articles from the first edition of the Annual Review of Linguistics are appearing online this week.  Bob Ladd, Dan Dediu and I wrote a review of correlations in linguistics.

We review a number of recent studies that have identified either correlations between different linguistic features (e.g., implicational universals) or correlations between linguistic features and nonlinguistic properties of speakers or their environment (e.g., effects of geography on vocabulary). We compare large-scale quantitative studies with more traditional theoretical and historical linguistic research and identify divergent assumptions and methods that have led linguists to be skeptical of correlational work. We also attempt to demystify statistical techniques and point out the importance of informed critiques of the validity of statistical approaches. Finally, we describe various methods used in recent correlational studies to deal with the fact that, because of contact and historical relatedness, individual languages in a sample rarely represent independent data points, and we show how these methods may allow us to explore linguistic prehistory to a greater time depth than is possible with orthodox comparative reconstruction.  Whether researchers are for or against these new techniques, understanding them is becoming increasingly necessary to interface with discussions in the field.

One of the most fun parts of putting the paper together was drawing this diagram (below) of all the links that we discuss.  It turns out that there are a lot of complicated links between linguistic and social variables!  I’m currently working on methods to disentangle this web.

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We also include three appendices as supplementary materials.  First, a list of electronic databases relevant for cross-cultural statistical comparisons.  Secondly, a very brief introduction to statistical hypothesis testing, which could be useful for linguists who are not familiar with statistical approaches.  Thirdly, a discussion of robustness and validity in statistical approaches to linguistics.

Other reviews also look interesting, for example, Johansson on Language abilities of Neandertals, Fisher and Vernes on genetics and linguistics, de Vos on village sign languages and Kroll et al. on bilingualism.

Ladd, D. R., Roberts, S. G., and Dediu, D. (2015). Correlational studies in typological and historical linguistics. Annual Review of Linguistics, 1(1). preview

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Mind-Culture Coevolution: Major Transitions in the Development of Human Culture and Society


This is revised from the introduction to a website I put up in the old days of web 1.0, all in hand-coded HTML. Where I’ve since uploaded downloadable versions of the documents I’ve used those links in this revised introduction, but you’re welcome to access the online versions from the old introduction.

Mind and Culture

A central phenomenon of the human presence on earth is that, over the long term, we have gained ever more capacity to understand and manipulate the physical world and, though some would debate this, the human worlds of psyche and society. The major purpose of the theory which the late David Hays and I have developed (and which I continue to develop) is to understand the mental structures and processes underlying that increased capacity. While more conventional students of history and of cultural evolution have much to say about what happened and when and what was influenced by what else, few have much to say about the conceptual and affective mechanisms in which these increased capacities are embedded. That is the story we have been endeavoring to tell.

Our theory is thus about processes in the human mind. Those processes evolve in tandem with culture. They require culture for their support while they enable culture through their capacities. In particular, we believe that the genetic elements of culture are to be found in the external world, in the properties of artifacts and behaviors, not inside human heads. Hays first articulated this idea in his book on the evolution of technology and I have developed it in my papers Culture as an Evolutionary Arena, Culture’s Evolutionary Landscape, in my book on music, Beethoven’s Anvil: Music in Mind and Culture, and in various posts at New Savanna and one for the National Humanities Center which I have aggregated into three working papers:

This puts our work at odds with some students of cultural evolution, especially those who identify with memetics, who tend to think of culture’s genetic elements as residing in nervous systems.

We have aspired to a system of thought in which the mechanisms of mind and feeling have discernible form and specificity rather than being the airy nothings of philosophical wish and theological hope. We would be happy to see computer simulations of the mechanisms we’ve been proposing. Unfortunately neither the computational art nor our thinking have been up to this task. But that, together with the neuropsychologist’s workbench, is the arena in which these matters must eventually find representation investigation, and a long way down the line, resolution. The point is that, however vague our ideas about mechanisms currently may be, it is our conviction that the phenomenon under investigation, culture and its implementation in the human brain, is not vague and formless, nor is it, any more, beyond our ken.

Major Transitions

The story we tell is one of cultural paradigms existing at four levels of sophistication, which we call ranks. In the terminology of current evolutionary biology, these ranks represent major transitions in cultural life. Rank 1 paradigms emerged when the first humans appeared on the savannas of Africa speaking language as we currently know it. Those paradigms structured the lives of primitive which societies emerged perhaps 50,000 to 100,000 years ago. Around 5,000 to 10,000 years ago Rank 2 paradigms emerged in relatively large stable human societies with people subsisting on systematic agriculture, living in walled cities and reading written texts. Rank 3 paradigms first emerged in Europe during the Renaissance and gave European cultures the capacity to dominate, in a sense, to create, world history over the last 500 years. This century has begun to see the emergence of Rank 4 paradigms. Continue reading

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Vyv Evans: The Human Meaning-Making Engine

If you read my last post here at Replicated Typo to the very end, you may remember that I promised to recommend a book and to return to one of the topics of this previous post. I won’t do this today, but I promise I will catch up on it in due time.

What I just did – promising something – is a nice example for one of the two functions of language which Vyvyan Evans from Bangor University distinguished in his talk on “The Human Meaning-Making Engine” yesterday at the UK Cognitive Linguistics Conference. More specifically, the act of promising is an example for the interactive function of language, which is of course closely intertwined with its symbolic function. Evans proposed two different sources for this two functions. The interactive function, he argued, arises from the human instinct for cooperation, whereas meaning arises from the interaction between the linguistic and the conceptual system. While language provides the “How” of meaning-making, the conceptual system provides the “What”. Evans used some vivid examples (e.g. this cartoon exemplifying nonverbal communication) to make clear that communication is not contingent on language. However, “language massively amplifies our communicative potential.” The linguistic system, he argued, has evolved as an executive control system for the conceptual system. While the latter is broadly comparable with that of other animals, especially great apes, the linguistic system is uniquely human. What makes it unique, however, is not the ability to refer to things in the world, which can arguably be found in other animals, as well. What is uniquely human, he argued, is the ability to symbolically refer in a sign-to-sign (word-to-word) direction rather than “just” in a sign-to-world (word-to-world) direction.  Evans illustrated this “word-to-word” direction with Hans-Jörg Schmid’s (e.g.  2000; see also here)  work on “shell nouns”, i.e. nouns “used in texts to refer to other passages of the text and to reify them and characterize them in certain ways.” For instance, the stuff I was talking about in the last paragraph would be an example of a shell noun.

According to Evans, the “word-to-word” direction is crucial for the emergence of e.g. lexical categories and syntax, i.e. the “closed-class” system of language. Grammaticalization studies indicate that the “open-class” system of human languages is evolutionarily older than the “closed-class” system, which is comprised of grammatical constructions (in the broadest sense). However, Evans also emphasized that there is a lot of meaning even in closed-class constructions, as e.g. Adele Goldberg’s work on argument structure constructions shows: We can make sense of a sentence like “Someone somethinged something to someone” although the open-class items are left unspecified.

Constructions, he argued, index or cue simulations, i.e. re-activations of body-based states stored in cortical and subcortical brain regions. He discussed this with the example of the cognitive model for Wales: We know that Wales is a geographical entity. Furthermore, we know that “there are lots of sheep, that the Welsh play Rugby, and that they dress in a funny way.” (Sorry, James. Sorry, Sean.) Oh, and “when you’re in Wales, you shouldn’t say, It’s really nice to be in England, because you will be lynched.”

On a more serious note, the cognitive models connected to closed-class constructions, e.g. simple past -ed or progressive -ing, are of course much more abstract but can also be assumed to arise from embodied simulations (cf. e.g. Bergen 2012). But in addition to the cognitive dimension, language of course also has a social and interactive dimension drawing on the apparently instinctive drive towards cooperative behaviour. Culture (or what Tomasello calls “collective intentionality”)  is contigent on this deep instinct which Levinson (2006) calls the “human interaction engine”. Evans’ “meaning-making engine” is the logical continuation of this idea.

Just like Evans’ theory of meaning (LCCM theory), his idea of the “meaning-making engine” is basically an attempt at integrating a broad variety of approaches into a coherent model. This might seem a bit eclectic at first, but it’s definitely not the worst thing to do, given that there is significant conceptual overlap between different theories which, however, tends to be blurred by terminological incongruities. Apart from Deacon’s (1997) “Symbolic Species” and Tomasello’s work on shared and joint intentionality, which he explicitly discussed, he draws on various ideas that play a key role in Cognitive Linguistics. For example, the distinction between open- and closed-class systems features prominently in Talmy’s (2000) Cognitive Semantics, as does the notion of the human conceptual system. The idea of meaning as conceptualization and embodied simulation of course goes back to the groundbreaking work of, among others, Lakoff (1987) and Langacker (1987, 1991), although empirical support for this hypothesis has been gathered only recently in the framework of experimental semantics (cf. Matlock & Winter forthc. – if you have an account at academia.edu, you can read this paper here). All in all, then, Evans’ approach might prove an important further step towards integrating Cognitive Linguistics and language evolution research, as has been proposed by Michael and James in a variety of talks and papers (see e.g. here).

Needless to say, it’s impossible to judge from a necessarily fairly sketchy conference presentation if this model qualifies as an appropriate and comprehensive account of the emergence of meaning. But it definitely looks promising and I’m looking forward to Evans’ book-length treatment of the topics he touched upon in his talk. For now, we have to content ourselves with his abstract from the conference booklet:

In his landmark work, The Symbolic Species (1997), cognitive neurobiologist Terrence Deacon argues that human intelligence was achieved by our forebears crossing what he terms the “symbolic threshold”. Language, he argues, goes beyond the communicative systems of other species by moving from indexical reference – relations between vocalisations and objects/events in the world — to symbolic reference — the ability to develop relationships between words — paving the way for syntax. But something is still missing from this picture. In this talk, I argue that symbolic reference (in Deacon’s terms), was made possible by parametric knowledge: lexical units have a type of meaning, quite schematic in nature, that is independent of the objects/entities in the world that words refer to. I sketch this notion of parametric knowledge, with detailed examples. I also consider the interactional intelligence that must have arisen in ancestral humans, paving the way for parametric knowledge to arise. And, I also consider changes to the primate brain-plan that must have co-evolved with this new type of knowledge, enabling modern Homo sapiens to become so smart.

 

References

Bergen, Benjamin K. (2012): Louder than Words. The New Science of How the Mind Makes Meaning. New York: Basic Books.

Deacon, Terrence W. (1997): The Symbolic Species. The Co-Evolution of Language and the Brain. New York, London: Norton.

Lakoff, George (1987): Women, Fire, and Dangerous Things. What Categories Reveal about the Mind. Chicago: The University of Chicago Press.

Langacker, Ronald W. (1987): Foundations of Cognitive Grammar. Vol. 1. Theoretical Prerequisites. Stanford: Stanford University Press.

Langacker, Ronald W. (1991): Foundations of Cognitive Grammar. Vol. 2. Descriptive Application. Stanford: Stanford University Press.

Levinson, Stephen C. (2006): On the Human “Interaction Engine”. In: Enfield, Nick J.; Levinson, Stephen C. (eds.): Roots of Human Sociality. Culture, Cognition and Interaction. Oxford: Berg, 39–69.

Matlock, Teenie & Winter, Bodo (forthc): Experimental Semantics. In: Heine, Bernd; Narrog, Heiko (eds.): The Oxford Handbook of Linguistic Analysis. 2nd ed. Oxford: Oxford University Press.

Schmid, Hans-Jörg (2000): English Abstract Nouns as Conceptual Shells. From Corpus to Cognition. Berlin, New York: De Gruyter (Topics in English Linguistics, 34).

Talmy, Leonard (2000): Toward a Cognitive Semantics. 2 vol. Cambridge, Mass: MIT Press.

 

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Adaptive languages: Population structure and lexical diversity

A new paper by Bentz et al. is available for preview here. It is about a correlation between the lexical diversity of languages and the presence of non-native speakers in a population. This is particularly relevant to the work by Lupyan & Dale (2010), who found that morphological complexity within a language correlates with the population size of a language. It’s reasonable to expect that the percentage of second language speakers within a population will be affected by the size of a speaker population. There has been a lot of talk on this blog in the past about correlations between population structure and linguistic structure. There’s a pretty comprehensive page here covering some of the (spurious) correlations covered on the blog in the past.  Bentz. et al. are however aware of the criticisms raised by Sean and James in their Plos one paper, and are all for a pluralistic approach and state that “there needs to be independent evidence for a causal relationship” before covering qualitative and quantitative evidence from other areas.

Here is the abstract for the interested:

Explaining the diversity of languages across the world is one of the central aims of historical  and evolutionary linguistics. This paper presents a quantitative approach to measure and  model a central aspect of this variation, namely the lexical diversity of languages. Lexical  diversity is defined as the breadth of word forms used to encode constant information content.  It is measured by means of comparing word frequency distributions for parallel translations of hundreds of languages. The measure is based on indices used in studies of biodiversity and in quantitative linguistics, i.e. Zipf-Mandelbrot’s law, Shannon entropy and type-token ratios. Three statistical models are given to elicit potential factors driving languages towards less diverse lexica. It is shown that the ratio of non-native speakers in languages predicts lower lexical diversity. This suggests that theories focusing on native acquisition as driving force of language change are incomplete. Instead, we argue that languages are information encoding systems shaped by the varying needs of their speakers. Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.

Culture, its evolution and anything inbetween