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                    <title>Hamburg Studies on Linguistic Diversity</title>
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                  <title>Transfer Effects in Multilingual Language Development</title>
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                  <jats:p>This volume, dedicated to language transfer, starts out with state-of-the-art psycholinguistic approaches to language transfer involving studies on psycho-typological transfer, lexical interference and foreign accent. The next chapter on Transfer in Language Learning, Contact, and Change presents new empirical data from several languages (English, German, Russian, French, Italian) on various transfer phenomena ranging from second language acquisition and contact-induced change in word order to cross-linguistic influences in word formation and the lexicon. Transfer in Applied Linguistics scrutinizes, on the one hand, the external sources of language transfer by investigating bilingual resources and the school context, but also by pointing out the differences in academic language in multilingual adolescents. On the other hand, internal sources of language transfer in multilingual classrooms are illuminated. A final chapter directs its focus on methodological issues that arise when more than one language is studied systematically and it offers a solution on causal effects for the investigation of heritage language proficiencies. The chapter also includes studies that exploit more innovative methodologies on L1 identification and clitic acquisition.</jats:p>
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                  <jats:p>This article focuses on automatic text classification which aims at identifying the first language (L1) background of learners of English. A particular question arising in the context of automated L1 identification is whether any features that are informative for a machine learning algorithm relate to L1-specific transfer phenomena. In order to explore this issue further, we discuss the results of a study carried out in the wake of a Native Language Identification Task. The task is based on the TOEFL11 corpus (cf. Blanchard et al. 2013), which involves a sample of 12,100 essays written by participants in the TOEFL® test from 11 different language backgrounds (Arabic, Chinese, French, German, Hindi, Italian, Japanese, Korean, Spanish, Telugu, and Turkish). The article will show our results in automatic L1 detection in the TOEFL11 corpus. These results are discussed in light of relevant transfer features which turned out to be particularly informative for automatic detection of L1 German and L1 Italian.</jats:p>
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