Culture, its evolution and anything inbetween
A cultural evolution approach to language suggests that genes encode weak prior biases that can be amplified through cultural transmission to produce strong language universals. Below is a diagram from Kirby, Dowman & Griffiths (2007).
Note the long-term feedback between language universals and genes. However, recent research is pointing towards a more complicated picture. Continue reading “Social structure and language evolution: resolving the synthetic/analytic debate”
Some peeps over the the University of York are organising a conference on the advances in visual methods for linguistics (AVML) to take place in September next year.
Some peeps over the the University of York are organising a conference on the advances in visual methods for linguistics (AVML) to take place in September next year. This might be of interest to evolutionary linguists who use things like phylogenetic trees, networks, visual simulations or other fancy dancy visual methods. The following is taken from their website:
Linguistics, like other scientific disciplines, is centrally reliant upon visual images for the elicitation, analysis and presentation of data. It is difficult to imagine how linguistics could have developed, and how it could be done today, without visual representations such as syntactic trees, psychoperceptual models, vocal tract diagrams, dialect maps, or spectrograms. Complex multidimensional data can be condensed into forms that can be easily and immediately grasped in a way that would be considerably more taxing, even impossible, through textual means. Transforming our numerical results into graphical formats, according to Cleveland (1993: 1), ‘provides a front line of attack, revealing intricate structure in data that cannot be absorbed in any other way. We discover unimagined effects, and we challenge imagined ones.’ Or, as Keith Johnson succinctly puts it, ‘Nothing beats a picture’ (2008: 6).
So embedded are the ways we visualize linguistic data and linguistic phenomena in our research and teaching that it is easy to overlook the design and function of these graphical techniques. Yet the availability of powerful freeware and shareware packages which can produce easily customized publication-quality images means that we can create visual enhancements to our research output more quickly and more cheaply than ever before. Crucially, it is very much easier now than at any time in the past to experiment with imaginative and innovative ideas in visual methods. The potential for the inclusion of enriched content (animations, films, colour illustrations, interactive figures, etc.) in the ever-increasing quantities of research literature, resource materials and new textbooks being published, especially online, is enormous. There is clearly a growing appetite among the academic community for the sharing of inventive graphical methods, to judge from the contributions made by researchers to the websites and blogs that have proliferated in recent years (e.g. Infosthetics, Information is Beautiful, Cool Infographics, BBC Dimensions, or Visual Complexity).
In spite of the ubiquity and indispensability of graphical methods in linguistics it does not appear that a conference dedicated to sharing techniques and best practices in this domain has taken place before. This is less surprising when one considers that relatively little has been published specifically on the subject (exceptions are Stewart (1976), and publications by the LInfoVisgroup). We think it is important that researchers from a broad spectrum of linguistic disciplines spend time discussing how their work can be done more efficiently, and how it can achieve greater impact, using the profusion of flexible and intuitive graphical tools at their disposal. It is also instructive to view advances in visual methods for linguistics from a historical perspective, to gain a greater sense of how linguistics has benefited from borrowed methodologies, and how in some cases the discipline has been at the forefront of developments in visual techniques.
So I thought I should begin my first post on here with a nice and gentle introductory sentence, but I realise that pointing out the increased use of computational phylogenetic tools on cultural and particularly linguistic data to the avid readers of this blog is probably a pretty pointless exercise.
There is of course a lot to say about parallels between biological and cultural evolution, and some of the work using computational tools has given us new insights into yet unanswered (and even hitherto unasked!) questions regarding language and language change. But today I’d like to share some thoughts on a particular “application” of phylogenetic tools, the methodology of which I find a bit odd, even though it is arguably the simplest evolutionary analogy of them all: using computational phylogenetics to reconstruct linguistic phylogenies.
Continue reading “Reconstructing linguistic phylogenies – a tautology?”
PZ Myers points to a TED video of Philip Zimbardo (see below) that links the declining academic performance of men with arousal addiction: here, the transition from boys to men in our modern society is characterised by “digitally rewired” brains that are in search of constant arousal etc etc. Like Myers, I’m sceptical of these claims, but I think they are certainly worth investigating, just not in the fashion employed by Susan Greenfield (you know, she of pseudo-neuroscientific fame). What I would like to see answered is: Do all Internet-influenced societies see this general trend of declining academic performance in men?
Another research question we might want to test, or control for in our hypothetical study, is whether or not there is a correlation between the number of female teachers and male academic performance? I haven’t bothered to look into the literature on this, so maybe a study has already been done, but female teachers certainly appear to outnumber their male counterparts in many corners of the globe (especially in primary school education). In Wales, for instance, I was astonished to find that 74.7% of teachers are female. My point: there might be a more obvious underlying cause as to why women are outperforming men, other than the rise of the zombie-generation of internet-addicted gamers. Still, I’m going to go with the cop-out approach and claim there are numerous factors underpinning male achievement (or lack of) in academia and beyond. I just wanted to point out that, in any study purporting to provide answers about declining educational attainment, you first really need to look at who is doing the teaching.
Continue reading “The Declining Academic Performance of Men”
A new paper in the journal ‘Emotion’ has presented research which has implications for the evolution of language, emotion and for theories of linguistic relativity.
A new paper in the journal ‘Emotion’ has presented research which has implications for the evolution of language, emotion and for theories of linguistic relativity. The paper, entitled ‘Categorical Perception of Emotional Facial Expressions Does Not Require Lexical Categories’, looks at whether our perception of other people’s emotions depend on the language we speak or if it is universal. The results come from the Max Planck Institute for Psycholinguistics and Evolutionary Anthropology.
Human’s facial expressions are perceived categorically and this has lead to hypotheses that this is caused by linguistic mechanisms.
The paper presents a study which compared German speakers to native speakers of Yucatec Maya, which is a language which has no labels which distinguish disgust from anger. This was backed up by a free naming task in which speakers of German, but not Yucatec Maya, made lexical distinctions between disgust and anger.
The study comprised of a match-to-sample task of facial expressions, and both speakers of German and Yucatec Maya perceived emotional facial expressions of disgust and anger, and other emotions, categorically. This effect was shown to be just as significant across the language groups, as well as across emotion continua (see figure 1.) regardless of lexical distinctions.
The results show that the perception of emotional signals is not the result of linguistic mechanisms which create different lexical labels but instead shows evidence that emotions are subject to their own biologically evolved mechanisms. Sorry Whorfians!
References
Sauter DA, Leguen O, & Haun DB (2011). Categorical perception of emotional facial expressions does not require lexical categories. Emotion (Washington, D.C.) PMID: 22004379
H/T: Evolutionary Linguistics.
Call deadline: 25 November 2011
Event Dates: 15-28 March 2012
Event Location: Durham, UK
Event URL:
http://www.dur.ac.uk/jeremy.kendal/EHBEA2012/Welcome.html
Dear colleagues,
We are organising a special themed session on language evolution at the 2012 Annual Meeting of the European Human Behaviour and Evolution Association, which is held in Durham, UK, 25th-28th March 2012 (http://www.dur.ac.uk/jeremy.kendal/EHBEA2012/Welcome.html). EHBEA is an excellent venue for interdisciplinary work on the cultural and biological evolution of human behaviour, including language. Given that EHBEA is running shortly after EVOLANG next year, we are happy for research that is targeted at EVOLANG to also be submitted here, although note that the audience for each is likely to be different.
If you would like to submit an abstract for consideration as part of this themed session, please follow the submission instructions on the EHBEA website, marking your abstract as for consideration in the language evolution special session, organised by Simon Kirby and Kenny Smith. Abstracts will be independently reviewed by the usual EHBEA reviewers, so bear that in mind when preparing your submission. The themed session will only run if sufficient abstracts are accepted – of course, papers on language evolution could be presented independently as standard EHBEA talks.
The deadline for submissions is November 25th.
PLEASE FORWARD THIS MESSAGE TO ANYONE WHO MIGHT BE INTERESTED!
Best wishes,
Simon & Kenny
A new paper in PlosOne has used new fancy research methods to look at whether humans are more capable of describing a word using just spoken communication, or whether the use of gesture also helps. This research is pertinent to the field of language evolution because it might help us understand if spoken language co-evolved with gesture as well as helping us understand how language is processed in the brain.
This new study builds on previous research in this area by using avatars in a virtual reality setting. Participants were either in control of the movements of their avatar, or not.
The study found that participants were much more successful in communicating concepts when the speaker was able to use their own gestures when explaining a concept using spoken language. The body language of the listener also impacted success at the task, showing the need for nonverbal feedback from the listener.
It’s worth noting that the primary purpose of this research wasn’t to find if gesture is helpful in communication (though that is certainly interesting and worthwhile) but rather whether using virtual reality is fruitful in these kinds of experiments.
The press release discusses some of the problems with using avatars:
The researchers note that there are limitations to nonverbal communication in virtual reality environments. First, they found that participants move much less in a virtual environment than they do in the “real world.” They also found that the perspective of the camera in the virtual environment affected the results.
Lead author, Dr. Trevor Dodds maintains, “this research demonstrates that virtual reality technology can help us gain a greater understanding of the role of body gestures in communication. We show that body gestures carry extra information when communicating the meaning of words. Additionally, with virtual reality technology we have learned that body gestures from both the speaker and listener contribute to the successful communication of the meaning of words. These findings are also important for the development of virtual environments, with applications including medical training, urban planning, entertainment and telecommunication.”
The work was led by Dr. Trevor Dodds at the Max Planck Institute for Biological Cybernetics in Germany.
A new paper in plos one, published today, has shown that experiments on human cognition needn’t be confined to the lab.
Experiments on human cognitive abilities, such as language, often rely on testing small and homogeneous groups of volunteers (mostly undergraduate students) coming to research facilities where they are asked to participate in behavioral experiments. This arrangement is not ideal as your sample will not be representative of the population as a whole and will also be restricted as there is only so many participants that money and time will allow you to get into the lab to be tested.
This new research by Dufau et al. shows that the sampling limitations which laboratory experiments produce can be overcome by using smartphones. Using smart phone technology, data can be collected for cognitive science experiments from thousands of subjects from all over the world.
To illustrate how this can be done the authors carried out a large-scale study using iPhone and iPads. This was a linguistic study looking at people’s ability to distinguish words from similar non-words.
The project, which began in December 2010 has managed to collect data from 4,157 subjects in just 4 months! This can be compared with the English Lexicon Project which acquired a similar volume of data using traditional methods which took more than 3 years.
The data was collected using applications which were produced in seven languages (English, Basque, Catalan, Dutch, French, Malay, Spanish). Smartphones can also support studies in alphabets other than Roman including Chinese, Greek, and Japanese. This creates the opportunity to create large-scale cross linguistic studies without even having to move from behind your desk.
Whilst the example here is linguistic there is every reason that smart phones can be implemented in looking at how universal other areas of cognitive behaviour are. Or even neurosceince and experimental philosophy. I wonder if it would be possible to carry out experiments using transmission chains using smart phones.
However, I do worry that using things like iPhones will have the same problems as using things like mechanical turk, as it means that experimenters will not be able to make sure that participants are carrying out the tasks properly and removes quite a lot of control. Smartphones are also still a luxury and therefore only people within a certain socio-economic class will have smartphones, so maybe these methods may not reach such a wide audience, which seems to be why they’re being proposed in the first place.
The authors of the paper are hailing smartphones “a potential revolution in cognitive science” but only time will tell if this really kicks off!
Reference
Stephane Dufau, Jon Andoni Dun abeitia, Carmen Moret-Tatay, Aileen McGonigal, David Peeters, F.-Xavier Alario, David A. Balota, Marc Brysbaert, Manuel Carreiras, Ludovic Ferrand, Maria Ktori, Manuel Perea, Kathy Rastle, Olivier Sasburg, Melvin J. Yap, J (2011). Smart Phone, Smart Science: How the Use of Smartphones Can Revolutionize Research in Cognitive Science PlosOne, 6 (9) : 10.1371/journal.pone.0024974
MIT recently held a symposium on the current status of AI, which apparently has seen precious little progress in recent decades. The discussion, it seems, ground down to a squabble over the prevalence of statistical techniques in AI and a call for a revival of work on the sorts of rule-governed models of symbolic processing that once dominated much of AI and its sibling, computational linguistics.
Briefly, from the early days in the 1950s up through the 1970s both disciplines used models built on carefully hand-crafted symbolic knowledge. The computational linguists built parsers and sentence generators and the AI folks modeled specific domains of knowledge (e.g. diagnosis in elected medical domains, naval ships, toy blocks). Initially these efforts worked like gang-busters. Not that they did much by Star Trek standards, but they actually did something and they did things never before done with computers. That’s exciting, and fun.
In time, alas, the excitement wore off and there was no more fun. Just systems that got too big and failed too often and they still didn’t do a whole heck of a lot.
Then, starting, I believe, in the 1980s, statistical models were developed that, yes, worked like gang-busters. And these models actually did practical tasks, like speech recognition and then machine translation. That was a blow to the symbolic methodology because these programs were “dumb.” They had no knowledge crafted into them, no rules of grammar, no semantics. Just routines the learned while gobbling up terabytes of example data. Thus, as Google’s Peter Norvig points out, machine translation is now dominated by statistical methods. No grammars and parsers carefully hand-crafted by linguists. No linguists needed.
What a bummer. For machine translation is THE prototype problem for computational linguistics. It’s the problem that set the field in motion and has been a constant arena for research and practical development. That’s where much of the handcrafted art was first tried, tested, and, in a measure, proved. For it to now be dominated by statistics . . . bummer.
So that’s where we are. And that’s what the symposium was chewing over.
Continue reading “Statistics and Symbols in Mimicking the Mind”
Didn’t I say that alcohol affects language evolution?
The video is actually a pretty good summary of many of the main issues surrounding cultural evolution and self domestication. Surprisingly, Bacardi have actually done some research on this:
I cannot wait to make a Bacardi-WALS data cocktail.
