A vivid commentary on Jewish survival and Jewish speech communities that will be enjoyed by the general reader, and is essential reading for students and researchers interested in the study of Middle Eastern languages, Jewish studies, and sociolinguistics.
Recent 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.