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Crossley 210 $aBristol ;$aBuffalo $cMultilingual Matters$dc2012 215 $a1 online resource (196 p.) 225 1 $aSecond language acquisition ;$v64 300 $aDescription based upon print version of record. 320 $aIncludes bibliographical references. 327 $tFrontmatter --$tContents --$tContributors --$t1. The Detection-Based Approach: An Overview --$t2. Detecting L2 Writers? L1s on the Basis of Their Lexical Styles --$t3. Exploring the Role of n-Grams in L1 Identification --$t4. Detecting the First Language of Second Language Writers Using Automated Indices of Cohesion, Lexical Sophistication, Syntactic Complexity and Conceptual Knowledge --$t5. Error Patterns and Automatic L1 Identification --$t6. The Comparative and Combined Contributions of n-Grams, Coh-Metrix Indices and Error Types in the L1 Classification of Learner Texts --$t7. Detection-Based Approaches: Methods, Theories and Applications 330 $aRecent work has pointed to the need for a detection-based approach to transfer capable of discovering elusive crosslinguistic effects through the use of human judges and computer classifiers that can learn to predict learners? language backgrounds based on their patterns of language use. This book addresses that need. It details the nature of the detection-based approach, discusses how this approach fits into the overall scope of transfer research, and discusses the few previous studies that have laid the groundwork for this approach. The core of the book consists of five empirical studies that use computer classifiers to detect the native-language affiliations of texts written by foreign language learners of English. The results highlight combinations of language features that are the most reliable predictors of learners? language backgrounds. 410 0$aSecond language acquisition (Clevedon, England) ;$v64. 606 $aLanguage transfer (Language learning) 606 $aEnglish language$xRhetoric$xStudy and teaching 610 $acomputer classifiers to detect language background. 610 $acrosslinguistic influence in SLA. 610 $acrosslinguistic influence. 610 $adetection-based approach. 610 $alearners? native-language backgrounds. 610 $atransfer in SLA. 610 $atransfer in language learning. 615 0$aLanguage transfer (Language learning) 615 0$aEnglish language$xRhetoric$xStudy and teaching. 676 $a401/.93 686 $aES 760$2rvk 701 $aJarvis$b Scott$f1966-$01501913 701 $aCrossley$b Scott A$01571442 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910779377603321 996 $aApproaching language transfer through text classification$93845849 997 $aUNINA LEADER 01028nam0 22002651i 450 001 UON00278480 005 20231205103826.899 100 $a20060609d1991 |0itac50 ba 101 $agre 102 $aGR 105 $a|||| 1|||| 200 1 $aAlexandros Papadiamantes$fG.K. 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