When looking at culture-driven population dynamics, a common assumption is that there’s a positive feedback between cultural evolution and demographic growth. The general prediction, then, is for unlimited growth in population and culture. Yet models based on these assumptions tend to ignore important aspects of cultural evolution, namely: (1) cultural transmission is not perfect; (2) culture does not always promote population growth. Ghirlanda et al (2010) incorporate these two features into a model, and arrive at some interesting conclusions. In particular, they argue those populations maintaining large amounts of culture may run the risk of extinction rather than stability or growth.
Recently, David Burkett and Tom Griffiths have looked at iterated learning of multiple languages from multiple teachers (Burkett & Griffiths 2010, see my post here). Here, I’ll describe a simpler model which allows bilingualism. I show that, counter-intuitively, bilingualism may be more stable than monolingualism.
As Niyogi & Berwick (2009) point out, there is a tendency in modelling of Linguistic Evolution to assume chains of single learners inheriting single grammars from single teachers. This is, of course, not realistic – we learn language from many people and people can speak more than one language. However, Niyogi & Berwick suggest deeper objections.
I always remember 2008 as the year when the entire UK media descended upon the former mining town of Bridgend. The reason: over the course of two years, 24 young people, most of whom were between the ages of 13 and 17, decided to commit suicide. At the time I was working in Bridgend, so I’m able to appreciate the claims of local MP, Madeleine Moon, that media influence had become part of problem. After all, most editors will tell you: the aim is to sell newspapers. And when this rule is rigorously applied, it should not come as a surprise at the depths some journalists will sink to recycle a news story. Even at a local-level, where you’d think some civic responsibility might exist, journalists clambered over themselves to find a new angle, generating ridiculous claims such as: electromagnetic waves from mobile phones caused the suicides.
For me, recent computational accounts of language evolution provide a compelling rationale that cultural, as opposed to biological, evolution is fundamental in understanding the design features of language. The basis for this rests on the simple notion of language being not only a conveyor of cultural information, but also a socially learned and culturally transmitted system: that is, an individual’s linguistic knowledge is the result of observing the linguistic behaviour of others. Here, this well-attested process of language acquisition, often termed Iterated Learning, emphasises the effects of differential learnability on competing linguistic variants. Sounds, words and grammatical structures are therefore seen to be the products of selection and directed mutation. As you can see from the use of terms such as selection and mutation it’s clear we can draw many parallels between the literature on language evolution and analogous processes in biology. Indeed, Darwin himself noted such similarities in the Descent of Man. However, one aspect evolutionary linguists don’t seem to borrow is that of a null model. Is it possible that the changes we see in languages over time are just the products of processes analogous to genetic drift?
I think the best place to start would be to state the following: Do not fear math. I spent far too long dodging equations and, when that wasn’t possible, freezing in a state of absolute confusion when faced with something like:
By the end of this post, you’ll hopefully be able to understand the above is not just a bunch of jibberish. Now before we get into the nitty gritty of the subject, I think a clarification of my assumptions is in order:
- That you’ll have a basic understanding of evolutionary biology. If not, then may I suggest Evolution as a very good, and highly comprehensive, introductory text. Failing that, you can always pop over to the wikipedia page.
- Although these posts will refer to evolutionary biology, my background is in linguistics and socio-cultural evolution — and as such, I will tend to default to the position of explaining these latter areas.
- It might sound insulting, but you’ll also need a basic understanding of math. You’ll be surprised by the number of people who, despite being very bright, lack even an elementary grasp of the fundamentals. A good place to start is with Kahn Academy’s wonderful online resource: http://www.khanacademy.org/.
- Having said that, I’m not really expecting anything beyond algebra level math, and I’ll do my best to try and clarify any confusions in the comments section. Also, I’m hardly a math guru, so I welcome anyone with a solid background in math to provide any hints, tips or suggestions, and, in the event I’m plain wrong, point out any mistakes.
I came across this rather amusing model for predicting football results using mostly economic data (click on image for full screen):
Now, we all know Brazil aren’t going to win the world cup, but most of us would’ve predicted they’d fare quite well, and possibly win it (my own failed prediction was with Argentina). What’s dubious about the algorithm their using is it predicted Serbia to be finalists! How the hell did they arrive at that conclusion? Well, to give you an indication they do discuss some of the factors included in the model. I’ll definitely be coming back to this when I’ve got a spare moment… They did, however, predict Germany would face, and subsequently knock out, England in the last 16.
If you think economic cuts are necessary, you’re being fooled. Martyn Winters (known to me as dad) writes about Joseph Stiglitz’s thoughts on George Osborne’s attempts to reduce the deficit:
You may have heard of Professor Joseph Stiglitz – he’s the Nobel laureate economist who correctly predicted the global crash. He’s distinctly unimpressed with Osbourne’s budget. This, he predicts, will make Britain’s recovery from recession longer, slower and harder than it needs to be. The rise in VAT could even tip us into a double-dip recession. He took time to offer George Osbourne a bit of advice – which will probably go unheeded, because Osbourne’s objectives aren’t necessarily to improve the economy. They are an ideological attack on the state, with the intention of shrinking it by forty percent.
The basis for this is part Keynesian, and has been echoed by other commentators such as Johann Hari, in that we must spend our way out of economic woes. Now I must admit I’m not too fond of how Osborne is going about reducing deficit (raising VAT… huh?), but, for reasons that’ll become apparent below, I do think we need to tackle the deficit.
Consider the bi-modal clapping that routinely rewards a successful performances—music, drama, circus, etc.—in eastern European communities, but which is less common in western Europe and North America. Z. Néda and colleagues (2000) have investigated this phenomenon, recording applause for a number of performances in Romania and Hungary. The applause would start out randomly and then quickly become strongly synchronized. Synchronized clapping would continue for a short while (one mode) and then disintegrate into random clapping (the other mode), from which synchronized clapping would reemerge, and so forth.
He also emphasises the importance of, and the need for, description in cultural evolution, drawing on Darwin’s own situation in the 19th Century:
Consider the situation of Darwin faced in the 19th century. When he began formulating his ideas on the origin of species he had three bodies of knowledge to work from: prior thought on the topic, his own observations over three decades, and the cumulative results of four centuries of descriptive work in natural history (cf. Ogilvie 2006) to which he had access through books and collections. That descriptive work provided models for his own observation and description. Plants and animals, and their lifeways, are very complex. Which traits and features are the most important to observe and describe? That is not an obvious matter, and it took naturalists decades to arrive the useful descriptive methods (cf. Foucault 1973, pp. 128 ff.). Secondly, it gave him the means to abstract and generalize from his own observations, to explore their implications throughout the natural world, most of which, of course, was beyond his immediate experience.
I’m planning on posting a comment tomorrow, but only if I’ve got something worth adding to the discussion. I think there are definitely areas worth looking at, such as the use of phylogenetic techniques in investigating culture, though I’m still juggling in my head whether they are entirely relevant to the conversation at hand. Also, be sure to check out John Wilkins’ comment about memes.
Here is a far-reaching and crucially relevant question for those of us seeking to understand the evolution of culture: Is there any relationship between population size and tool kit diversity or complexity? This question is important because, if met with an affirmative answer, then the emergence of modern human culture may be explained by changes in population size, rather than a species-wide cognitive explosion. Some attempts at an answer have led to models which make certain predictions about what we expect to see when populations vary. For instance, Shennan (2001) argues that in smaller populations, the number of people adopting a particular cultural variant is more likely to be affected by sampling variation. So in larger populations, learners potentially have access to a greater number of experts, which means adaptive variants are less likely to be lost by chance (Henrich, 2004).
Models aside, and existing empirical evidence is limited with the results being mixed. I previously mentioned the gradual loss of complexity in Tasmanian tool kits after the population was isolated from mainland Australia. Elsewhere, Golden (2006) highlighted the case of isolated Polar Inuit, who lost kayaks, the bow and arrow and other technologies when their knowledgeable experts were wiped out during a plague.Yet two systematic studies (Collard et al., 2005; Read, 2008) of the Inuit case found no evidence for population size being a predictor of technological complexity.