demography – Replicated Typo

Some quick announcements

Just thought I’d make three quick announcements:

First, I decided to drag myself into the age of 140-characters and (albeit begrudgingly) joined Twitter. I say begrudgingly because my day is already packed with plenty of distractions besides adding Twitter into the mix… But I noticed it’s the place where all the cool science bloggers are gathering, and gradually coagulating into an amorphous cloud of science networking, so I thought I might as well sign up (ever the follower, never the trendsetter).

Second, if you happen to find yourself in Edinburgh on Friday October 1st, then you can come and see me and Sean presenting our respective posters (click here and here for the abstracts) at the 24th Language at Edinburgh Lunch. I’m sure, for me at least, it’ll be quite a sobering experience in highlighting how little I know about phonology, phonetics, sociolinguistics and demography. On the plus side I’ll get some free food 🙂 .

Lastly, if you happened to click on my poster abstract, then the more observant of you will have noticed I’m now affiliated with Cardiff University. Yes, that’s right, I’m doing yet another masters course. This time it’s at the Centre for Language and Communication Research, with the idea being that I’ll get a more solid foundation in research methodology etc before pursuing a PhD or research assistant position.

That is all.

Alcohol Consumption affects Morphological Complexity

I previously talked about how changes in the demography of learners can affect the cultural evolution of a language. The hypothesis is that language adapts to the balance between declarative and procedural memory users. Since alcohol consumption affects procedural but not declarative memory (Smith & Smith, 2003), we might expect to see communities that have a high alcohol consumption using less complex morphology.

I find that communities that have a morphologically marked future tense have significantly higher alcohol consumption than communities that have a lexically marked future tense (Alcohol consumption data from WHO, language structure data from World atlas of language structures, 198 languages, t = 14.8, p<0.0001). This statistic does not take into account many factors, but is meant as a motivation for further research into language structure and social structure.

Smith C, & Smith D (2003). Ingestion of ethanol just prior to sleep onset impairs memory for procedural but not declarative tasks. Sleep, 26 (2), 185-91 PMID: 12683478

Phoneme Inventory Size and Demography

It’s long since been established that demography drives evolutionary processes (see Hawks, 2008 for a good overview). Similar attempts are also being made to describe cultural (Shennan, 2000; Henrich, 2004; Richerson & Boyd, 2009) and linguistic (Nettle, 1999a; Wichmann & Homan, 2009; Vogt, 2009) processes by considering the effects of population size and other demographic variables. Even though these ideas are hardly new, until recently, there was a ceiling as to the amount of resources one person could draw upon. In linguistics, this paucity of data is being remedied through the implementation of large-scale projects, such as WALS, Ethnologue and UPSID, that bring together a vast body of linguistic fieldwork from around the world. Providing a solid direction for how this might be utilised is a recent study by Lupyan & Dale (2010). Here, the authors compare the structural properties of more than 2000 languages with three demographic variables: a language’s speaker population, its geographic spread and the number of linguistic neighbours. The salient point being that certain differences in structural features correspond to the underlying demographic conditions.

With that said, a few months ago I found myself wondering about a particular feature, the phoneme inventory size, and its potential relationship to underlying demographic conditions of a speech community. What piqued my interest was that two languages I retain a passing interest in, Kayardild and Pirahã, both contain small phonological inventories and have small speaker communities. The question being: is their a correlation between the population size of a language and its number of phonemes? Despite work suggesting at such a relationship (e.g. Trudgill, 2004), there is little in the way of empirical evidence to support such claims. Hay & Bauer (2007) perhaps represent the most comprehensive attempt at an investigation: reporting a statistical correlation between the number of speakers of a language and its phoneme inventory size.

In it, the authors provide some evidence for the claim that the more speakers a language has, the larger its phoneme inventory. Without going into the sub-divisions of vowels (e.g. separating monophthongs, extra monophtongs and diphthongs) and consonants (e.g. obstruents), as it would extend the post by about 1000 words, the vowel inventory and consonant inventory are both correlated with population size (also ruling out that language families are driving the results). As they note:

That vowel inventory and consonant inventory are both correlated with population size is quite remarkable. This is especially so because consonant inventory and vowel inventory do not correlate with one another at all in this data-set (rho=.01, p=.86). Maddieson (2005) also reports that there is no correlation between vowel and consonant inventory size in his sample of 559 languages. Despite the fact that there is no link between vowel inventory and consonant inventory size, both are significantly correlated with the size of the population of speakers.

Using their paper as a springboard, I decided to look at how other demographic factors might influence the size of the phoneme inventory, namely: population density and the degree of social interconnectedness.

Continue reading “Phoneme Inventory Size and Demography”

New Blog: Culture Evolves!

… Well, new to me at least. It’s run by Fiona Jordan of the Max Planck Institute for Psycholinguistics, and her latest post is an interview with one of my favourite researchers, Simon Greenhill (I didn’t know he designed a sudoku solving program). Also, after having done a little digging into her publications, I found the following forthcoming paper: The effect of population size and density on rates of linguistic evolution. Here is the abstract:

Evolutionary theory from population genetics predicts that demography may play an important role in determining the rate at which cultural and linguistic traits change over time. However, relatively few studies have explored this relationship for language at an appropriate scale and in a quantitative way, nor controlled for the problem of non-independence induced by the historical relationships between languages. Here we use phylogenetic trees of 351 Austronesian languages to test whether the rate of change in core vocabulary is affected by population size and population density. We detected a strong phylogenetic signal in both population size and density, indicating the need for historical control. We find a significant inverse relationship between lexical replacement and population size, no relationship with population density, and we confirm that splitting events influence lexical evolution. These results support the idea that a process analogous to genetic drift may be an important factor in lexical evolution. Furthermore, the strong phylogenetic signal in these demographic factors suggests that despite repeated population splits the social conditions that influence speech community size and density are maintained and inherited from one generation to the next.

I’m not going to say anything on a paper I haven’t yet read, other than it looks pretty cool and that more people should be considering the influence of demographic factors in linguistics.

Population Size and Rates of Language Change

In previous posts, I’ve looked at the relationship between cultural evolution and demography (see here, here and here). As such, it makes sense to see if such methods are applicable in language which is, after all, a cultural product. So, having spent the last few days looking over the literature on language and demography, I found the following paper on population size and language change (free download). In it, the authors, Søren Wichmann and Eric Holman, use lexical data from WALS to test for an effect of the number of speakers on the rate of language change. Their general findings argue against a strong influence of population size, with them instead opting for a model where the type of network influences change at a local level, through different degrees of connectivity between individuals. Here is the abstract:

Previous empirical studies of population size and language change have produced equivocal results. We therefore address the question with a new set of lexical data from nearly one-half of the world’s languages. We first show that relative population sizes of modern languages can be extrapolated to ancestral languages, albeit with diminishing accuracy, up to several thousand years into the past. We then test for an effect of population against the null hypothesis that the ultrametric inequality is satisified by lexical distances among triples of related languages. The test shows mainly negligible effects of population, the exception being an apparently faster rate of change in the larger of two closely related variants. A possible explanation for the exception may be the influence on emerging standard (or cross-regional) variants from speakers who shift from different dialects to the standard. Our results strongly indicate that the sizes of speaker populations do not in and of themselves determine rates of language change. Comparison of this empirical finding with previously published computer simulations suggests that the most plausible model for language change is one in which changes propagate on a local level in a type of network in which the individuals have different degrees of connectivity.

As I’m in the middle of several other things at the moment I don’t really have time to provide a thorough review of this paper. Having said that, I agree with their claim of population size being unlikely to account for rates of language change. I reckon their results would be stronger if they factored in population density. So those that are dense and large will change faster than those which are large and distributed. The main point being that population size and population density influence the degree of social interconnectivity. Nettle (1999), for instance, argues that “spreading an innovation over a tribe of 500 people is much easier and takes much less time than spreading one over five million people.” This is fairly reasonable if we are looking at the generation of a single innovation within each of these populations. However, if those 500 people are spread across a large distance, then their transmission chain is going to be stretched: effectively lowering the rate of transmission. The same applies for a population of five million individuals who are packed into a small area: Arguably, given the right conditions, we can arrive at a situation where a population of five million show greater levels of interconnectivity than 500. I think it’s this aspect, the level of social interconnectivity, which may be more relevant to the rate of language change (other things to test for, include: writing systems/literacy and inter-language contact).

Culture-driven population dynamics: sustainable or unsustainable?

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.

Continue reading “Culture-driven population dynamics: sustainable or unsustainable?”

There's definitely something wrong with your model when Serbia are finalists

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.

Population size predicts technological complexity in Oceania

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.

Continue reading “Population size predicts technological complexity in Oceania”

Experiments in cultural transmission and human cultural evolution

For those of you familiar with the formal mathematical models of cultural evolution (Cavalli-Sforza & Feldman, 1981; Boyd & Richerson, 1985), you’ll know there is a substantive body of literature behind the process of cultural transmission. It comes as a surprise, then, that experiments in this area are generally lacking.

For instance, if we look at evolutionary biology, then there are many experiments into small-scale microevolutionary processes, such as natural selection, sexual selection, mutation and drift, which are then applied in showing how these processes generate population-level, macroevolutionary patterns. It follows then, that this sort of population-level thinking can be applied to cultural evolution: the forces and biases of cultural transmission can be studied experimentally to see if they fit with population-level patterns of cultural change documented by scientists. As the current paper by Mesoudi & Whiten (2008) notes, this potentially gives cultural transmission experiments added significance: “cultural transmission should not only be studied for its own sake (i.e. in order to better understand cultural transmission itself), but also in order to explain broader cultural patterns and trends, all as part of a unified science of cultural evolution”.

Continue reading “Experiments in cultural transmission and human cultural evolution”

The Movius Line represents the crossing of a demographic threshold

When examining the dispersal of Pleistocene hominins, one of the more fascinating debates concern the patterns of biological and technological evolution in East Asia and other regions of the Old World. One suggestion emerging from palaeoanthropological research places a demarcation between these two regions in the form of a geographical division known as the Movius Line. Specifically, the suggestions that initially led to the Movius Line were based on observations of differing technological patterns, namely: the lack of Acheulean handaxes and the Levallois core traditions in East Asia.

Since Hallam L. Movius’ initial proposal, the recent discovery of handaxes within East Asia have led to suggestions that the Movius Line is in fact obsolete. Suggesting this may not in fact be the case is a recent paper by Stephen Lycett & Christopher Norton, which highlights three central points coming from a growing body of research: 1) “several morphometric analyses have identified statistically significant differences between the attributes of specific biface assemblages from east and west of the Movius Line”; 2) “The number of sites from which handaxes have been recovered in East Asia tend to be geographically sparse compared with many regions west of the Movius Line”; 3) “‘handaxe’ specimens tend only to comprise a small percentage of the total number of artefacts recovered, a situation that contrasts with many classic Acheulean sites in western portions of the Old World, where bifacial handaxes may dominate assemblages in large numbers”.

Continue reading “The Movius Line represents the crossing of a demographic threshold”