Wednesday, 11 November 2009

Codeswitching as a Move to Markedness

One advantage of having two languages is having an extra tool with which to avoid ambiguity. For example, in English, ‘Thirteen’ and ‘Thirty’ are often confused, while in German ‘dreizehn’ and ‘dreissig’ are more different, while in Chinese ‘三十’ and ‘十 三’ are very different. Montanari (2008, pp. 622) gives an example of this tactic in a trilingual child (KAT) interacting with their grandmother (GRA) in Spanish and Tagalog:

%sit : KAT and GRA are engaged in book reading
*KAT : [‘ota].
%gls : pelota
%eng : ball in Spanish
*GRA : ¿botas ? zapatos ? zapatos.
%eng : boots ? shoes ? shoes.
*KAT : bola bola !
%eng : ball in Tagalog
*GRA : ah la pelota ahí detrá s, ahí está la pelota.
%eng : ah the ball right behind, there is the ball.

Because the child cannot pronounce the ‘pel’ of ‘peloa’ (ball), their attempt is confused with ‘botas’ (shoes). Instead of attempting the word again, or using pragmatics, the child uses the word in a different language. This makes it easier to pronounce and thus easier to understand. Perhaps, then, some codeswitching can be accounted for by this tactic.

One might assume that the optimal strategy, given two different languages, is to switch at every word. However, individual languages tend to display a move to markedness (Shillcock, Hick, Cairns, Chater & Levy, 1995). This principle is ‘that when consonant interactions introduce phonological ambiguity, the ambiguity introduced is always in the direction of a less frequent phoneme’ (Tamariz & Shillcock, 2001). That is, frequently occurring words should be optimised for pronunciation within a language, while words from another language will be free from this pressure. This suggests that frequent constructions (e.g. Noun Phrases) should be most salient in the same language. However, at larger phrase/constituent boundaries, where the probability of words co-occurring is less, words from other languages may be more salient. Code-switching phenomena such as Myer-Scotton’s embedded language frames may fall out of this interaction.

A modelling approach could be used to investigate this. A list of cognates and sentence templates in two languages will be required. Sentence templates will be filled with words from either language, based on maximising the phonetic distinctness of the sentence. This will be calculated using Markov Chain assumptions, with words as nodes and transition costs as the phonetic difference between the last phone of the current word and the first phone of the next word. To model this for children, extra costs could be imposed on transitions to words with complex consonant clusters.

This will produce sentences which are maximally phonetically distinct. Inferences about the choice of language could be drawn over many sentences and many sentence types, with particular attention being paid to constituent boundaries.

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