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dc.contributor.advisorCornish, Hannahen
dc.contributor.authorTinits, Peeteren
dc.date.accessioned2014-03-20T11:10:11Z
dc.date.available2014-03-20T11:10:11Z
dc.date.issued2012-11-28
dc.identifier.urihttp://hdl.handle.net/1842/8429
dc.description.abstractThe dissertation reports on a series of experiments that were conducted to establish a novel paradigm for investigating proximal mechanisms of diffusion in language simplification. The paradigm implements a semiotic matching task with learned miniature languages in a closed group in order to investigate how such language simplification would fare in the presence of an established community speaking a moderately complex language. For this, composite populations were made of three subjects, with one subject receiving a different training than the other two, representing minority and majority varieties respectively. Exploratory analyses on several pilot studies are reported and their implications for the experimental setup explained. The main experiment contrasts two minority varieties (one simple, one complex) in the presence of a majority complex variety, in order to test the hypothesis that a simple variety would prove more stable in such contact situations. The results indicate that the simple variety exhibited less change when comparing the languages on training with the final round of play (one-tailed t-test p < 0.01). Interestingly, this stability was not accompanied by a quicker success in establishing communication, in fact, the groups with a simple variety did worse. The findings warrants further studies into such communicative situations with a larger sample sizes, and the main aim of the dissertation is to provide a platform to begin from.en
dc.language.isoen
dc.publisherThe University of Edinburghen
dc.subjectartificial language learningen
dc.subjectcomplex populationsen
dc.subjectlanguage changeen
dc.subjectlanguage complexityen
dc.titleLanguage Simplification in Composite Populations: Experimental Approachen
dc.typeThesis or Dissertationen
dc.type.qualificationlevelMastersen
dc.type.qualificationnameMSc Master of Scienceen
dcterms.accessRightsRestricted Accessen


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