Please join us on Friday, August 21 for the newest in the LSA's "Meet the Authors" webinars showcasing research from our flagship journal, Language.  The webinar will take place from 11:00 AM - 12:30 PM U.S. Eastern Time.  

Authors Jennifer Culbertson, Marieke Schouwstra, and Simon Kirby of the University of Edinburgh discussed their article, "From the world to word order: deriving biases in noun phrase order from statistical properties of the world."

Panelist slides

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Please read on for author biographies and an abstract.   The article is available on the Project MUSE page for Language through the LSA's publish-ahead-of-print initiative. 

The Authors

Jennifer Culbertson's research focuses on understanding how languages are shaped by learning and use. She is interested in how typological universals (differences in the frequency of linguistic patterns across the world's languages) arise from properties of our cognitive system. To get at this, she teaches people (children and adults) miniature artificial languages, and creates computational models of their behavior. (Picured at right)

 

Marieke Schouwstra is interested in how individual and cultural processes interact to give us structured languages that allow us to share our thoughts. She studies this by focusing on what happens when languages are created anew, in laboratory experiments in which participants communicate in novel ways. Currently at the University of Edinburgh, she will soon take up a position at the University of Amsterdam. (Pictured at left)

 

Simon Kirby is Professor of Language Evolution at the University of Edinburgh and Fellow of the British Academy, the Royal Society of Edinburgh, and the Cognitive Science Society. He works in parallel on scientific and artistic investigations of cultural evolution and the origins of human uniqueness. He founded the Centre for Language Evolution, which has pioneered techniques for growing languages in the lab and in computer simulation. His artistic work includes the BAFTA-winning Cybraphon, which is now part of the permanent collection of the National Museum of Scotland. (Pictured at right)

 
 
The Abstract
 
The world's languages exhibit striking diversity. At the same time, recurring linguistic patterns suggest the possibility that this diversity is shaped by features of human cognition. One well-studied example is word order in complex noun phrases (like these two red vases). While many orders of these elements are possible, a subset appear to be preferred. It has been argued that this order reflects a single underlying representation of noun phrase structure, from which preferred orders are straightforwardly derived (e.g. Cinque 2005). Building on previous experimental evidence using arti ficial language learning by Culbertson & Adger (2014), we show that these preferred orders arise not only in existing languages, but also in improvised sequences of gestures produced by English speakers. We then use corpus data from a wide range of languages to argue that the hypothesized underlying structure of the noun phrase might be learnable from statistical features relating objects and their properties conceptually. Using an information-theoretic measure of strength of association, we nd that adjectival properties (e.g. red) are on average more closely related to the objects they modify (e.g. wine), than numerosities (e.g. two), which are in turn more closely related to the objects they modify than demonstratives (e.g. this). It is exactly those orders which transparently reflect this|by placing adjectives closest to the noun, and demonstratives farthest away|which are more common across languages, and preferred in our silent gesture experiments. These results suggest that our experience with objects in the world, combined with a preference for transparent mappings from conceptual structure to linear order, can explain constraints on noun phrase order.