Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-13T09:30:24.423Z Has data issue: false hasContentIssue false
  • English
  • Français

Languages adapt to their contextual niche

Published online by Cambridge University Press:  25 November 2014

JAMES WINTERS ,
SIMON KIRBY  and
KENNY SMITH
JAMES WINTERS*
Affiliation:
School of Philosophy, Psychology, and Language Sciences, University of Edinburgh, United Kingdom
SIMON KIRBY
Affiliation:
School of Philosophy, Psychology, and Language Sciences, University of Edinburgh, United Kingdom
KENNY SMITH
Affiliation:
School of Philosophy, Psychology, and Language Sciences, University of Edinburgh, United Kingdom
*
†Address for correspondence: e-mail: J.R.Winters@sms.ed.ac.uk
Get access Rights & Permissions [Opens in a new window]

Abstract

It is well established that context plays a fundamental role in how we learn and use language. Here we explore how context links short-term language use with the long-term emergence of different types of language system. Using an iterated learning model of cultural transmission, the current study experimentally investigates the role of the communicative situation in which an utterance is produced (situational context) and how it influences the emergence of three types of linguistic systems: underspecified languages (where only some dimensions of meaning are encoded linguistically), holistic systems (lacking systematic structure), and systematic languages (consisting of compound signals encoding both category-level and individuating dimensions of meaning). To do this, we set up a discrimination task in a communication game and manipulated whether the feature dimension shape was relevant or not in discriminating between two referents. The experimental languages gradually evolved to encode information relevant to the task of achieving communicative success, given the situational context in which they are learned and used, resulting in the emergence of different linguistic systems. These results suggest language systems adapt to their contextual niche over iterated learning.

Keywords

cultural transmissioniterated learninglanguage evolutioncontextcommunication games
Type
Research Article
Information
Language and Cognition , Volume 7 , Issue 3 , September 2015 , pp. 415 - 449
Check for updates
Copyright
Copyright © UK Cognitive Linguistics Association 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

references

Altmann, E. G., Pierrehumbert, J. B., & Motter, A. E. (2011). Niche as a determinant of word fate in online groups. PLoS ONE, 6(5), e19009. doi:10.1371/journal.pone.0019009.Google Scholar
Ay, N., Flack, J. C., & Krakauer, D. C. (2007). Robustness and complexity co-constructed in multimodal signaling networks. Philosophical Transactions of the Royal Society B, 362, 441–447.Google Scholar
Baayen, R. H. (2008). Analyzing linguistic data: a practical introduction to statistics using R. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Bach, K. (2012). Context dependence (such as it is). In Garcia-Carpintero, M. & Kolbel, M. (Eds.), The Continuum companion to the philosophy of language, online <http://userwww.sfsu.edu/kbach/Bach.ContextDependence.pdf>.Google Scholar
Bates, D. M., Maechler, M., & Bolker, B. (2012). lme4: linear mixed-effects models using S4 classes. R package version 0.999999-0, online <http://www.citeulike.org/group/17044/article/12173300>..>Google Scholar
Beckner, C., Blythe, R., Bybee, J., Christiansen, M. H., Croft, W. … Schoenemann, T. (2009). Language is a complex adaptive system: position paper. Language Learning, 59, 1–26.Google Scholar
Beuls, K., & Steels, L. (2013). Agent-based models of strategies for the emergence and evolution of grammatical agreement. PLoS ONE 8(3), e58960. doi: 10.1371/journal.pone.0058960.CrossRefGoogle ScholarPubMed
Bleys, J., & Steels, L. (2009). Linguistic selection of language strategies – a case study for colour. ECAL, 2, 150–157.Google Scholar
Bratman, M. (1992). Shared cooperative activity. Philosophical Review, 101, 327–341.Google Scholar
Brighton, H., Kirby, S., & Smith, K. (2005). Cultural selection for learnability: three principles underlying the view that language adapts to be learnable. In Tallerman, M. (Ed.), Language origins: perspectives on evolution (Chapter 13). Oxford: Oxford University Press.Google Scholar
Bybee, J. (2010). Language, usage and cognition. Cambridge: Cambridge University Press.Google Scholar
Caldwell, C. A., & Smith, K. (2012). Cultural evolution and perpetuation of arbitrary communicative conventions in experimental microsocieties. PLoS ONE, 7(8), e43807. doi: 10.1371/journal.pone.0043807.Google Scholar
Chafe, W. (1976). Giveness, contrastiveness, definiteness, subjects, topics and point of view. In Li, Charles N. (Ed.), Subject and topic (pp. 25–56). New York: Academic Press.Google Scholar
Christiansen, M. H., & Chater, N. H. (2008). Language as shaped by the brain. Behavioral and Brain Science, 31(5), 489–508.Google Scholar
Clark, H. H. (1996). Using language. Cambridge: Cambridge University Press.Google Scholar
Cornish, H., Tamariz, M., & Kirby, S. (2009). Complex adaptive systems and the origins of adaptive structure: what experiments can tell us. Language Learning (Special Issue on Language as a Complex Adaptive System), 59(s1), 187–205.Google Scholar
Croft, W. (2000). Explaining language change: an evolutionary approach. Harlow: Longman.Google Scholar
Culbertson, J., & Adger, D. (2014). Language learners privilege structured meaning over surface frequency. PNAS, 111(16), 5842–5847.Google Scholar
Culbertson, J., Smolensky, P., & Wilson, C. (2013). Cognitive biases, linguistic universals, and constraint-based grammar learning. Topics in Cognitive Science, 5(3), 392–424.Google Scholar
Dingemanse, M., Torreira, F., & Enfield, N. J. (2013). Is ‘Huh?’ a universal word? Conversational infrastructure and the convergent evolution of linguistic items. PLoS ONE, 8(11), e78273. doi:10.1371/journal.pone.0078273.CrossRefGoogle Scholar
Du Bois, J. W. (1987). The discourse basis of ergativity. Language, 63(4), 805–855.Google Scholar
Dunn, M., Greenhill, S. J., Levinson, S. C., & Gray, R. D. (2011). Evolved structure of language shows lineage-specific trends in word-order universals. Nature, 473, 79–82.Google Scholar
Evans, N., & Levinson, S. C. (2009). The myth of language universals: language diversity and its importance for cognitive science. Behavioral and Brain Sciences, 32(5), 429–492.Google Scholar
Evans, V. (2005). The meaning of time: polysemy, the lexicon and conceptual structure. Journal of Linguistics, 41, 33–75.Google Scholar
Evans, V., & Green, M. (2006). Cognitive linguistics: an introduction. Edinburgh: Edinburgh University Press.Google Scholar
Fay, N., & Ellison, T. M. (2013). The cultural evolution of human communication systems in different sized populations: usability trumps learnability. PLoS ONE, 8(8), e71781. doi:10.1371/journal.pone.0071781.Google Scholar
Fedzechkina, M., Jaeger, T. F., & Newport, E. L. (2012). Language learners restructure their input to facilitate efficient communication. PNAS, 109, 17897–17902.Google Scholar
Ferreira, V., Slevc, L., & Rogers, E. (2005). How do speakers avoid ambiguous linguistic expressions? Cognition, 96(3), 263–284.Google Scholar
Fery, C., & Krifka, M. (2008). Information structure: notional distinctions, ways of expression. In Sterkenburg, Piet van (Ed.), Unity and diversity of languages (pp. 123–136). Amsterdam: John Benjamins.CrossRefGoogle Scholar
Frank, M. C., & Goodman, N. D. (2012). Predicting pragmatic reasoning in language games. Science, 336, 998. doi: 10.1126/science.1218633.CrossRefGoogle ScholarPubMed
Galantucci, B., Garrod, S., & Roberts, G. (2012). Experimental Ssemiotics. Language and Linguistics Compass, 6, 477–493.Google Scholar
Galantucci, B., Kroos, C., & Rhodes, T. (2010). The effects of rapidity of fading on communication systems. Interaction Studies, 11, 100–111.Google Scholar
Garrod, S., Fay, N., Lee, J., Oberlander, J., & MacLeod, T. (2007). Foundations of representation: Where might graphical symbol systems come from? Cognitive Science, 31, 961–987.Google Scholar
Geeraerts, D. (1993). Vagueness’s puzzles, polysemy’s vagaries. Cognitive Linguistics, 4(3), 223–272.Google Scholar
Grice, H. P. (1957). Meaning. Philosophical Review, 66, 377–388.Google Scholar
Griffiths, T. L., & Kalish, M. (2007). Language evolution by iterated learning with Bayesian agents. Cognitive Science, 31, 441–480.Google Scholar
Heine, B., Claudi, U., & Hünnemeyer, F. (1991). Grammaticalization: a conceptual framework. Chicago: University of Chicago Press.Google Scholar
Hoefler, S. H. (2009). Modelling the role of pragmatic plasticity in the evolution of linguistic communication. Unpublished PhD thesis, University of Edinburgh.Google Scholar
Hopper, P. J., & Traugott, E. C. (2003). Grammaticalization (Cambridge Textbooks in Linguistics). Cambridge: Cambridge University Press.Google Scholar
Kirby, S. (1999). Function, selection and innateness: the emergence of language universals. Oxford: Oxford University Press.Google Scholar
Kirby, S. (2012). Language is an adaptive system. the role of cultural evolution in the origins of structure. In Tallerman, M. & Gibson, K. R. (Eds.), The Oxford handbook of language evolution (pp. 589–604). Oxford: Oxford University Press.Google Scholar
Kirby, S., Cornish, S., & Smith, K. (2008). Cumulative cultural evolution in the laboratory: an experimental approach to the origins of structure in human language. PNAS, 105, 10681–10686.CrossRefGoogle Scholar
Kirby, S., & Hurford, J. (2002). The emergence of linguistic structure: an overview of the iterated learning model. In Cangelosi, A. & Parisi, D. (Eds.), Simulating the evolution of language (pp. 121–148). London: Springer Verlag.Google Scholar
Lass, R. (1997). Historical linguistics and language change. Cambridge: Cambridge University Press.Google Scholar
Levinson, S. (2000). Presumptive meanings: the theory of generalised conversational implicature. Cambridge, MA: MIT Press.Google Scholar
Lewis, M., Sugarman, E., & Frank, M. C. (2014). The structure of the lexicon reflects principles of communication. In Bello, P., Guarini, M., McShane, M., & Scassellati, B. (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society, online <http://langcog.stanford.edu/papers/LF-cogsci2014.pdf>.Google Scholar
Lupyan, G., & Dale, R. (2010). Language structure is partly determined by social structure. PLoS ONE, 5(1), e8559. doi: 10.1371/journal.pone.0008559.Google Scholar
Lyons, J. (1977). Semantics. Cambridge: Cambridge University Press.Google Scholar
Miller, G. A. (1951). Language and communication. New York: McGraw-Hill Book Company.Google Scholar
Perfors, A., & Navarro, D. J. (2014). Language evolution can be shaped by the structure of the world. Cognitive Science, 38(4), 775–793.Google Scholar
Piantadosi, S. T., Tily, H., & Gibson, E. (2012). The communicative function of ambiguity in language. Cognition, 122, 280–291.Google Scholar
Pinker, S., & Bloom, P. (1990). Natural language and natural selection. Behavioral and Brain Sciences, 13, 707–784.Google Scholar
R Core Team. (2013). R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.Google Scholar
Ramscar, M., Yarlett, D., Dye, M., Denny, K., & Thorpe, K. (2010). The effects of Feature-Label-Order and their implications for symbolic learning. Cognitive Science, 34, 909–957.CrossRefGoogle ScholarPubMed
Reali, F., & Griffiths, T. L. (2009). The evolution of linguistic frequency distributions: relating regularisation to inductive biases through iterated learning. Cognition, 111, 317–328.Google Scholar
Scott-Phillips, T. C., & Kirby, S. (2010). Language evolution in the laboratory. Trends in Cognitive Sciences, 14(9), 411–417.Google Scholar
Scott-Phillips, T. C., Kirby, S., & Ritchie, G. R. S. (2009). Signalling signalhood and the emergence of communication. Cognition, 113(2), 226–233.Google Scholar
Sedivy, J. C. (2005). Evaluating explanations for referential context effects: evidence for Gricean mechanisms in online language interpretation. In Trueswell, J. C. & Tanenhaus, M. K. (Eds.), Approaches to studying world-situated language use: bridging the language as product and language as action traditions (pp. 153–171). Cambridge, MA: MIT Press.Google Scholar
Selten, R., & Warglien, M. (2007). The emergence of simple languages in an experimental coordination game. PNAS, 104, 7361–7366.Google Scholar
Silvey, C., Kirby, S., & Smith, K. (2014). Word meanings evolve to selectively preserve relevant distinctions over cultural transmission. Cognitive Science. doi: 10.1111/cogs.12150.Google Scholar
Smith, K., Tamariz, M., & Kirby, S. (2013). Linguistic structure is an evolutionary trade-off between simplicity and expressivity. In Knauff, M., Pauen, M., Sebanz, N., & Wachsmuth, I. (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 1348–1353). Austin, TX: Cognitive Science Society.Google Scholar
Smith, K., & Wonnacott, E. (2010). Eliminating unpredictable variation through iterated learning. Cognition, 116, 444–449.Google Scholar
Sperber, D., & Wilson, D. (1995). Relevance: communication and cognition (2nd ed.). Oxford/Cambridge: Blackwell Publishers.Google Scholar
Steels, L. (2003). Evolving grounded communication for robots. Trends in Cognitive Sciences, 7(7), 308–312.CrossRefGoogle ScholarPubMed
Steels, L. (2012). Self-organization and selection in cultural language evolution. In Steels, Luc (Ed.), Experiments in cultural language evolution (pp. 1–37). Amsterdam: John Benjamins.Google Scholar
Thiesen-White, C., Kirby, S., & Oberlander, J. (2011). Integrating the horizontal and vertical cultural transmission of novel communication systems. In Carlson, L., Hölscher, C., & Shipley, T. (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 956–961). Austin, TX: Cognitive Science Society.Google Scholar
Tomasello, M. (2008). Origins of human communication. Cambridge, MA: MIT Press.Google Scholar
Traugott, E., & Konig, E. (1991). The semantics-pragmatics of grammaticalization revisited. In Traugott, Elizabeth & Heine, Bernd (Eds.), Approaches to grammaticalization (pp. 189–218). Amsterdam: John Benjamins.Google Scholar
Traugott, E., & Trousdale, G. (2013). Constructionalization and constructional changes. Oxford: Oxford University Press.Google Scholar
Tuggy, D. (1993). Ambiguity, polysemy and vagueness. Cognitive Linguistics, 4, 273–291.Google Scholar
Verhoef, T. (2012). The origins of duality of patterning in artificial whistled languages. Language and Cognition, 4(4), 357–380.Google Scholar
Wedgwood, D. (2007). Shared assumptions: semantic minimalism and relevance theory. Journal of Linguistics, 43, 647–681.Google Scholar
Wray, A., & Grace, G. W. (2007). The consequences of talking to strangers: evolutionary corollaries of socio-cultural influences on linguistic form. Lingua, 117, 543–578.Google Scholar
Zipf, G. (1949). Human behavior and the principle of least effort. New York: Addison-Wesley.Google Scholar