Icon for: D Russell Richie


University of Connecticut
Years in Grad School: 2
Judges’ Queries and Presenter’s Replies
  • May 21, 2013 | 09:16 a.m.

    I am not a language researcher, but borrowing from research in other domains, it seems that your finding—that a richer exchange/connectivity accelerates convergence—is unsurprising. is this not the case in language development/research?

  • Icon for: D Russell Richie

    D Russell Richie

    Lead Presenter
    May 21, 2013 | 03:46 p.m.

    Hi, Ayelet! Thanks for your question.

    Actually, there have been other simulations (unconnected to empirical data!) of similar (but not identical!) language convergence processes showing that the star network (here, the homesign network) is no less efficient than networks with higher clustering coefficients (basically, networks with greater inter-connectivity, like the NSL-type network; Gong et al., 2011). And there have been some experiments similarly showing that the effect of network topology on participants’ performance depends heavily on the task — low average path length and high clustering coefficients hasten performance in a consensus coloring game, but slow performance in a contrast coloring game (Judd et al., 2010). So, we can’t say whether some network structure is generally ‘more efficient’ than others — it can really differ by task, in sometimes surprising ways.

    But even for a task like ours, there is reason to suspect, a priori, that the star network would be more efficient — the hub of the star network COULD serve as the standard of form, to whom everyone else adjusts. One could imagine that in the NSL-type network, it is hard for anything to be conventionalized, because there is no clear ‘leader’ to impose conventions. And in fact, there has been some experimental work suggesting that asymmetries in roles (i.e., one person clearly leading, the other following) actually assist conventionalization (Selten & Warglien, 2007). So in all, I don’t think the results are entirely obvious a priori!

  • May 23, 2013 | 08:20 p.m.

    Thanks, I may agree :-)

  • May 21, 2013 | 11:18 a.m.

    To what extent does evidence indicate that convergence can be productively changed by overt means (schools, for example), in contrast to the more naturalistic convergence that you have shown for the families and communities?

  • Icon for: D Russell Richie

    D Russell Richie

    Lead Presenter
    May 21, 2013 | 03:56 p.m.

    Hi, Eileen! Thanks for your questions. And greetings from Nicaragua, where we are about to collect more data for this project!

    We actually have good reason to think that overt means did not play a big role in NSL’s emergence. While NSL actually emerged in a school setting, the school was just a magnet — it didn’t impart any signs to the kids. The teachers did not know what kids were doing, and when they eventually figured out generally what the kids were doing, they didn’t learn the signs (which is not good for Deaf education in Nicaragua, but that’s another story…). Moreover, the overt/top-down means that I DID mention in the poster, i.e. the standardizations seminars, could only happen after enough bottom-up convergence occurred so that people could say “Okay, we all agree on this sign…let’s go into the country and share it”.

  • May 21, 2013 | 06:30 p.m.

    How might you expect language to evolve with the increased connectivity provided by texting and the internet compared to traditional forms of spoken and written communication?

  • Icon for: D Russell Richie

    D Russell Richie

    Lead Presenter
    May 21, 2013 | 07:40 p.m.

    Hi, Kristopher. It’s a good question. It’s really hard to know, but I think there are a number of things that could happen. Our results, at least, would suggest that increasing inter-connectivity would hasten conventionalization, and lead to less dialectal variation. On the other hand, I have read a few times that texting, twitter, and other modern media are in some cases actually saving minority languages from extinction, as it enables languages to be written down and shared widely at minimal cost. At any rate, it’s an interesting question, and I look forward to seeing what happens!

  • Icon for: Mary Gauvain

    Mary Gauvain

    May 21, 2013 | 07:11 p.m.

    I have two related questions: (1) How do your results and proposed processes fit with language changes previously described in the literature regarding the shift from a pidgin to a creole language? (2) How does the age of the language learner affect the processes you study?

  • Icon for: D Russell Richie

    D Russell Richie

    Lead Presenter
    May 23, 2013 | 12:29 a.m.

    Hi Mary. Thanks for your questions! I apologize for responding late. As I mentioned in another reply, we are collecting data in Nicaragua right now, and I don’t have constant access to email.

    (1) Homesign and NSL are both, in many regards, like spoken language pidgins and creoles — individuals that have no common language get/got together and have/had to devise a new communication system! And we see pidgin/creole-like properties and processes in homesign and NSL, and indeed in signed languages more broadly. For example (and this gets to your second question), it seems that each wave of child learners of NSL have regularized the language, or ‘creolized’ it, in a number of ways, e.g. how gestural space is used for syntax. Another interesting but less certain possibility: it has been claimed that creoles do not have much morphology (structure internal to the word, e.g. im-poss-ible has three ‘morphemes’, or meaningful components). At the same time, many people have claimed that sign languages do not have much in the way of sequential morphology (as opposed to simultaneous morphology, i.e. conveying different pieces of information simultaneously with handshape, location, movement, etc.). What linguists debate, however, is whether this is due to (a) the youth of signed languages (the oldest one I know of is Turkish Sign Language, ca. 600 years old. Contrast that with the 1000’s of years back that we can trace spoken languages) and the fact that they have creolized recently, or (b) something about the visual-gestural modality (e.g. that visual memory traces decay more rapidly than auditory memory traces).

    But homesign and NSL are, I think, somewhat more striking examples of pidginization/creolization, because they are examples of language creation de novo — the Deaf individuals did not bring different, preexisting sign languages to the task of creating a new signed language!

    (2) As for the role of child learners in the specific processes our study speaks to, it is a good possibility that children, who regularized other aspects of language, accelerated conventionalization of the lexicon. Our data can’t speak to this right now (we don’t have a large enough sample to test for these kind of individual differences), but this is something my research group and I have thought about.

  • May 22, 2013 | 09:03 p.m.

    Wow, this is fascinating. I’m really interested in evolutionary processes of symbolic emergence and cultural change. One of the benefits of an ABM is that you get to test scenarios that you cannot measure directly, as well as the group-level outcomes of individual level processes or measurements. To me it is not surprising that more connections creates a faster symbolic convergence. Is it faster per network link? I doubt it.

    My question is about language emergence and diversification, and is related to Kristopher’s question. Social identity also emerges dynamically from individual interactions over time in a population, but social identities also tend to diverge over time in a large population. Because social identity restricts communication flow, language follows the same patterns. Thus social identity is key to language stability, but so is limited interconnections with other social groups. Could you speculate on the relative influence of social identity and increasing interconnection on language diversity over the long term?

  • May 22, 2013 | 09:08 p.m.

    Also, Russell, I wonder if you have considered any ABM fitting approaches? Measuring individual behavioral variables and then fitting ABM network parameters, say, to the individual outcomes. This can be a very powerful inference engine. NetLogo’s BehaviorSearch does this sort of thing. Best, Tim

Presentation Discussion
  • Icon for: Brian Drayton

    Brian Drayton

    Faculty: Project Co-PI
    May 20, 2013 | 08:52 a.m.

    Very interesting and valuable methodology. Raises lots of questions, of course. Maybe most important (in my mind) is the role of the lexicon within the language as a whole. Once you’ve got even a rudimentary lexicon, then the process of converging on a new entry seems a more constrained problem — but how does this model relate to the “convergence” on syntax (say)? (What’s your position on Universal Grammar?)

    Another question is the phonology (or in this case the gestural components) — the example in your video (’milking") is a prime example of an “onomatopoetic” coinage — the lexicalization constitutes in this case a process of creating and refining a representation of something with very clearly visible/comparable characters. So not yet a model for the “emergence of language,” as I understand it, but lexicons are themselves rather complex and fascinating phenomena. Very promising work!
  • Icon for: D Russell Richie

    D Russell Richie

    Lead Presenter
    May 20, 2013 | 01:52 p.m.

    Thanks for your questions and kind words, Brian! Yes, as the lexicon solidifies, a phonology (system governing the combination of forms to create words), will emerge, and that will certainly constrain the creation of additional words. As for how this model relates to convergence of syntax, my coauthor Charles Yang actually first used a very related model for children’s acquisition of syntax. In that model, when a child hears a sentence, they probabilistically choose a particular grammar (say, a grammar that allows subject-dropping vs one that does not) with which to parse the sentence. They then try to parse the sentence with that grammar, and if they are successful, they increase the probability of selecting that grammar in the future. So, something similar to that might be applied to emergence (rather than acquisition) of syntax! As for Universal Grammar, I remain somewhat agnostic, and our work actually skirts the matter somewhat. That is, we can’t really say whether the lexicon convergence that we see here relies on some language-specific cognitive machinery.

    Yes, most of the signs we observe are quite iconic (their form resembles their meaning)! This is actually quite common in sign languages’ early stages. Over time, however, as the signs shift to fit in the emerging phonology (for signed languages: the handshapes, locations, movements, palm orientations, and sometimes facial expressions allowed in the language, as well as the constraints governing their combination, e.g. that a non-dominant hand must mirror the dominant hand or stay still), and as they reduce in form to become easier to produce, they tend to lose their iconicity. As an example, the American Sign Language sign for FEEL used to be produced over the heart, but now it is produced over the center of the chest (it has centralized — a common historical change in signed languages). So something like this could happen in homesign, and very likely is happening/did happen in Nicaraguan Sign Language. Conventionalization is a key part of this process — when everyone recognizes the sign, they no longer need iconicity to understand it, and the form of the sign can shift a bit.

    But actually, I would say that iconicity in itself is not an un-linguistic property. Making a sign be iconic does not in itself reduce its combinatorial capacity, or any other deeper linguistic qualities, in any considerable way. Iconicity is only short-lived in the language if, as I mentioned, its form does not fit with the rest of the phonology. Otherwise, it can stick around, as it does in many signed and spoken language (Japanese, for example, has an extensive sound symbolism system: http://en.wikipedia.org/wiki/Japanese_sound_sym...).

  • May 20, 2013 | 11:59 p.m.

    Very creative video, I love how you have the videos on the whiteboard.

  • Icon for: D Russell Richie

    D Russell Richie

    Lead Presenter
    May 21, 2013 | 03:24 a.m.

    Thanks, Stephanie!

  • May 23, 2013 | 03:44 p.m.

    This is really interesting. I study humpback whales and one particularly mind-blowing area of research is how whales sing the same song during the breeding season and how this song evolves within or between seasons. During fall in Alaska, other researchers tell me we can hear an early less refined form of the song but by the time whales get to Hawaii its fully developed. Without knowing much about this field, I wonder whether your model could predict this convergence.

  • Icon for: William Snyder

    William Snyder

    Faculty: Project Co-PI
    May 23, 2013 | 04:03 p.m.

    I have a question about the computer simulations you ran. It seems to me that there’s a confound between number of interactions occurring in a fixed period of time, and the number of dyads that are interacting during that period of time. Have you looked at the number of pairwise exchanges required to reach convergence, as well the number of time steps required?

  • May 23, 2013 | 06:55 p.m.

    Really ingenuous and refreshing video concept! Exciting emphasis on the larger push you are making at the end of the video- it really is super important that we start using empirical models to start evaluating natural datasets. Great project!

  • Further posting is closed as the event has ended.