How old am I?

It’s my birthday!  But how old am I?  Well, that’s not such a straightforward question.  Even a seemingly well-defined concept such as age can be affected by cultural factors

First, my age in years is a bit of an estimate of the actual amount of time I’ve been alive, due to leap-years etc.  Second, a year is a culturally determined (although not all that arbitrary) amount of time.  But these are petty squabbles.

There are bigger differences.  For instance, there are cultural differences when it comes to the recall of birth dates.  And I’m not talking about saying you’re 24 when you’re 68.  Matched comparisons of age reporting in death certificates and census data found minimal differences for white Americans (Hill et al., 2000) but nearly half were inconsistent for African-Americans (Hill et al., 1997). These may be due to economic differences.

Furthermore, the definition of age can vary cross-culturally.  Knodel & Chyovan (1991) surveyed women between the ages of 15 and 49 in Thailand.  As well as finding that up to 20% reported an age that was more than one year different to their actual age, they surmised that most calculated their age as difference between the present year and the year of their birth, disregarding whether their birthday had passed.


So in some parts of the world I’ve been 26 for four months now, or was it 25?


Hill, M., Preston, S., Elo, I., & Rosenwaike, I. (1997). Age-Linked Institutions and Age Reporting among Older African Americans Social Forces, 75 (3) DOI: 10.2307/2580528

Hill, M., Preston, S., & Rosenwaike, I. (2000). Age Reporting among White Americans Aged 85+: Results of a Record Linkage Study Demography, 37 (2) DOI: 10.2307/2648119

Knodel J, & Chayovan N (1991). Age and birth date reporting in Thailand. Asian and Pacific population forum / East-West Population Institute, East-West Center, 5 (2-3) PMID: 12343437

From Natyural to Nacheruhl: Utterance Selection and Language Change

Most of us should know by now that language changes. It’s why the 14th Century prose of Geoffrey Chaucer is nearly impenetrable to modern day speakers of English. It is also why Benjamin Franklin’s phonetically transcribed pronunciation of the English word natural sounded like natyural (phonetically [nætjuɹəl]) rather than our modern variant with a ch sound (phonetically [nætʃəɹəl]). However, it is often taken for granted on this blog that language change can be understood as an evolutionary process. Many people might not see the utility of such thinking outside the realm of biology. That is, evolutionary theory is strictly the preserve of describing biological change, and is less useful as a generalisable concept. A relatively recent group of papers, however, have taken the conceptual machinery of evolutionary theory (see Hull, 2001) and applied it to language.

It's all natyural, yo!

Broadly speaking, these utterance selection models highlight that language change occurs across two steps, each corresponding to an evolutionary process: (1) the production of an utterance, and (2) the propagation of linguistic variants within a speech community. The first of these, the production of an utterance, takes place across an extremely short timescale: we will replicate particular sounds, words, and constructions millions of times across our production lifetime. It is as this step where variation is generated: phonetic variation, for instance, is not only generated through different speakers having different phonetic values for a single phoneme — the same speaker will produce different phonetic values for a single phoneme based on the context. Through variation comes the possibility of selection within a speech community. This leads us to our second timescale, which sees the selection and propagation of these variants — a process that may “take many generations of the replication of the word, which may–or may not–extend beyond the lifetime of an individual speaker.” (Croft, in press).

Recent mathematical work in this area has highlighted four selection mechanisms: replicator selection, neutral evolution, neutral interactor selection, and weighted interactor selection. I’ll now provide a brief overview of each of these mechanisms in relation to language change.

Continue reading “From Natyural to Nacheruhl: Utterance Selection and Language Change”

Mutual Exclusivity in the Naming Game

The Categorisation Game or Naming Game looks at how agents in a population converge on a shared system for referring to continuous stimuli (Steels, 2005; Nowak & Krakauer, 1999). Agents play games with each other, one referring to an object with a word and the other trying to guess what object the first agent was referring to. Through experience with the world and feedback from other agents, agents update their words. Eventually, agents are able to communicate effectively.  The model is usually couched in terms of agents trying to agree on labels for colours (a continuous meaning space).  In this post I’ll show that the algorithms used have implicit mutual exclusivity biases, which favour monolingual viewpoints.  I’ll also show that this bias is not necessary and obscures some interesting insights into evolutionary dynamics of langauge.

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Genetic Anchoring, Tone and Stable Characteristics of Language

In 2007, Dan Dediu and Bob Ladd published a paper claiming there was a non-spurious link between the non-derived alleles of ASPM and Microcephalin and tonal languages. The key idea emerging from this research is one where certain alleles may bias language acquisition or processing, subsequently shaping the development of a language within a population of learners. Therefore, investigating potential correlations between genetic markers and typological features may open up new avenues of thinking in linguistics, particularly in our understanding of the complex levels at which genetic and cognitive biases operate. Specifically, Dediu & Ladd refer to three necessary components underlying the proposed genetic influence on linguistic tone:

[…] from interindividual genetic differences to differences in brain structure and function, from these differences in brain structure and function to interindividual differences in language-related capacities, and, finally, to typological differences between languages.”

That the genetic makeup of a population can indirectly influence the trajectory of language change differs from previous hypotheses into genetics and linguistics. First, it is distinct from attempts to correlate genetic features of populations with language families (e.g. Cavalli-Sforza et al., 1994). And second, it differs from Pinker and Bloom’s (1990) assertions of genetic underpinnings leading to a language-specific cognitive module. Furthermore, the authors do not argue that languages act as a selective pressure on ASPM and Microcephalin, rather this bias is a selectively neutral byproduct. Since then, there have been numerous studies covering these alleles, with the initial claims (Evans et al., 2004) for positive selection being under dispute (Fuli Yu et al., 2007), as well as any claims for a direct relationship between dyslexia, specific language impairment, working memory, IQ, and head-size (Bates et al., 2008).

A new paper by Dediu (2010) delves further into this potential relationship between ASPM/MCPH1 and linguistic tone, by suggesting this typological feature is genetically anchored to the aforementioned alleles. Generally speaking, cultural and linguistic processes will proceed on shorter timescales when compared to genetic change; however, in tandem with other recent studies (see my post on Greenhill et al., 2010), some typological features might be more consistently stable than others. Reasons for this stability are broad and varied. For instance, word-use within a population is a good indicator of predicting rates of lexical evolution (Pagel et al., 2007). Genetic aspects, then, may also be a stabilising factor, with Dediu claiming linguistic tone is one such instance:

From a purely linguistic point of view, tone is just another aspect of language, and there is no a priori linguistic reason to expect that it would be very stable. However, if linguistic tone is indeed under genetic biasing, then it is expected that its dynamics would tend to correlate with that of the biasing genes. This, in turn, would result in tone being more resistant to ‘regular’ language change and more stable than other linguistic features.

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Memory, Social Structure and Language: Why Siestas affect Morphological Complexity

Children are better than adults at learning second languages.  Children find it easy, can do it implicitly and achieve a native-like competence.  However, as we get older we find learning a new language difficult, we need explicit teaching and find some aspects difficult to master such as grammar and pronunciation.  What is the reason for this?  The foremost theories suggest it is linked to memory constraints (Paradis, 2004; Ullman, 2005).  Children find it easy to incorporate knowledge into procedural memory – memory that encodes procedures and motor skills and has been linked to grammar, morphology and pronunciation.  Procedural memory atrophies in adults, but they develop good declarative memory – memory that stores facts and is used for retrieving lexical items.  This seems to explain the difference between adults and children in second language learning.  However, this is a proximate explanation.  What about the ultimate explanation about why languages are like this?

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More on The Social Sensitivity Hypothesis

This post was chosen as an Editor's Selection for ResearchBlogging.orgIn a recent post, James wrote about the Social Sensitivity hypothesis.  Given findings that certain genetic variants will make a person more sensitive to social contact and more reliant on social contact under stress, it proposes that certain genetic variants ‘fit’ better with certain social structures.  In support of this idea, Way and Lieberman (2010) find a correlation between the prevalence of this variant and the level of collectivism (as opposed to individualism) in a society.

An alternative explanation I’ve been thinking about is migration patterns.  If genetic differences make a person less reliant on social networks, they may be more likely to migrate.  This would predict that areas settled later in human history will have more ‘non socially sensitive’ individuals.

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More on Phoneme Inventory Size and Demography

On the basis of Sean’s comment, about using a regression to look at how phoneme inventory size improved as geographic spread was incorporated along with population size, I decided to look at the stats a bit more closely (original post is here). It’s fairly easy to perform multiple regression in R, which, in the case of my data, resulted in highly significant results (p<0.001) for the intercept, area and population (residual standard error = 9.633 on 393 degrees of freedom; adjusted R-Squared = 0.1084). I then plotted all the combinations as scatterplots for each pair of variables. As you can see below, this is fairly useful as a quick summary but it is also messy and confusing. Another problem is that the pairs plot is on the original data and not the linear model.

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Some Links #17: The Return of Whorf

The famous Klingon linguist, Whorf, has returned with his theories on linguistic relativity (I know, terrible joke).

The Largest Whorfian Study Ever. The Lousy Linguist looks at the paper Ways to go: Methodological considerations in Whorfian studies on motion events. As you can probably guess, the paper deals with the methodological issues surrounding linguistic relativity. It’s all interesting stuff, bringing to light important questions about how the brain handles language. I’m fairly lay when it comes to this topic, so for more background on the current events, see similar posts over at Language Log: Never Mind the Conclusions, What’s the Evidence? and SLA Blog: Linguistic Relativity, Whorf, Linguistic Relativity.

But Science Doesn’t Work That Way: Miller & Chomsky (1963). Many of you who read this blog will be familiar with the position taken by Melody’s post over at Child’s Play: against a strong nativist position in language acquisition. It’s the first part in a series of posts so I’ll reserve judgement on her conclusions until she’s finished. But much of her post is drawn from a brilliant paper by Scholz and Pullum (2005): Irrational Nativist Exuberance. Key paragraph:

Do we really want to say that phonemes are ‘innate’?

I haven’t yet addressed how we know — with all but certainty — that the model Miller and Chomsky used had to be a poor approximation of human learning capabilities.  It has to do with phonemes.

Experiments have shown that people are remarkably sensitive to the transitional probabilities between phonemes in their native languages, both when speaking and when listening to speech.  If Miller and Chomsky’s assessment of probabilistic learning is correct, then the problem of “parameter estimation” should apply not only to learning the probabilities between words, but also to learning the probabilities between phonemes.  Given that people do learn to predict phonemes, Miller and Chomsky’s logic would force us to conclude that not only must ‘grammar’ be innate, but the particular distribution of phonemes in English (and every other language) must be innate as well.

We only get to this absurdist conclusion because Miller & Chomsky’s argument mistakes philosophical logic for science (which is, of course, exactly what intelligent design does).  So what’s the difference between philosophical logic and science? Here’s the answer, in Einstein’s words, “No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”

PLoS Blogs. Yet another blogging network. This time it’s with the Public Library of Science. The most notable move, for me at least, is Neuroanthropology. That move hasn’t seemed to impact upon their ability to produce good articles, the latest of which being in regards to Uner Tan Syndrome (I’m sure there was a documentary about this on BBC…).

Hap Map 3: more people ~ more genetic variation. Razib has a cool read on the new HapMap dataset. The current paper (Integrating common and rare genetic variation in diverse human populations) looked for variants across the genome in 11 populations, consisting of 1184 samples. It’s been especially useful with less common variants. As with previous versions, you can also explore the data. Here’s the conclusion from the paper:

With improvements in sequencing technology, low-frequency variation is becoming increasingly accessible. This greater resolution will no doubt expand our ability to identify genes and variants associated with disease and other human traits. This study integrates CNPs and lower-frequency SNPs with common SNPs in a more diverse set of human populations than was previously available. The results underscore the need to characterize population-genetic parameters in each population, and for each stratum of allele frequency, as it is not possible to extrapolate from past experience with common alleles. As expected, lower-frequency variation is less shared across populations, even closely related ones, highlighting the importance of sampling widely to achieve a comprehensive understanding of human variation.

Mathematics: From the Birth of Numbers. Someone gave this in to the charity store I work at: it’s a brilliant book by Jan Gullberg on (surprise, surprise) the history of mathematics. The first chapter was on mathematics and language, so I had to pick it up, and not just for that chapter alone, as there are plenty of gaps in my mathematical knowledge I’m sure this will clear up.

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”

The Problem With a Purely Adaptationist Theory of Language Evolution

According to the evolutionary psychologist Geoffrey Miller and his colleagues (e.g Miller 2000b), uniquely human cognitive behaviours such as musical and artistic ability and creativity, should be considered both deviant and special. This is because traditionally, evolutionary biologists have struggled to fathom exactly how such seemingly superfluous cerebral assets would have aided our survival. By the same token, they have observed that our linguistic powers are more advanced than seems necessary to merely get things done, our command of an expansive vocabulary and elaborate syntax allows us to express an almost limitless range of concepts and ideas above and beyond the immediate physical world. The question is: why bother to evolve something so complicated, if it wasn’t really all that useful?

Miller’s solution is that our most intriguing abilities, including language, have been shaped predominantly by sexual selection rather than natural selection, in the same way that large cumbersome ornaments, bright plumages and complex song have evolved in other animals. As one might expect then, Miller’s theory of language evolution has been hailed as a key alternative to the dominant view that language evolved because it conferred a distinct survival advantage to its users through improved communication (e.g. Pinker 2003). He believes that language evolved in response to strong sexual selection pressure for interesting and entertaining conversation because linguistic ability functioned as an honest indicator of general intelligence and underlying genetic quality; those who could demonstrate verbal competence enjoyed a high level of reproductive success and the subsequent perpetuation of their genes. Continue reading “The Problem With a Purely Adaptationist Theory of Language Evolution”