Cross-linguistic influence in structures at the syntax-discourse interface as a window into grammatical change

该项目研究双语儿童和成人的跨语言影响，作为历史语言变化的潜在驱动力。特别是，我们专注于双语儿童和成人是否可以影响改变语法模式，作为他们的经验输入的结果。我们假设，这是一个模型的接触引起的跨语言的影响，可能已经发生在历史上，从而导致永久的语言变化随着时间的推移。因此，这个项目探讨了在个人和语言系统中观察到的变化之间的联系。我们的研究采用启动方法，主要关注两种结构：与格交替结构和动宾结构交替结构。我们研究了儿童和成人的德英和法英双语者的跨语言影响潜力，以回答以下研究问题：（1）启动是否揭示了一个心理语言过程，可以作为历史语言变化的基础，如果是的话，如何？(2)不同年龄的双语者之间的启动效应的差异是否可以解释与历史语言变化相关的发展差异？第一个问题涉及研究单元的关键特征1“语言习得，处理和变化中的输入结构化”（SILPAC），而第二个问题涉及关键特征2。这些问题将根据调节论点结构信息使用的不同因素（关键特征3）进行检查，目的是推进实验过程和模型，以理解变化（关键特征4）。

This project investigates cross-linguistic influence in bilingual children and adults as a potential driver of historical language change. In particular, we focus on whether bilingual children and adults can be influenced to change grammatical patterns as a result of the input they experience. We assume that this is a model for the kind of contact-induced cross-linguistic influence that could have occurred in history and thus resulted in permanent language change over time. Thus, this project explores the link between changes observed in the individual and the language system. Our studies use priming methods and focus on two structures: the dative alternation and the verb-particle construction alternation. We examine the potential for cross-linguistic influence in child and adult German-English and French-English bilinguals in order to answer the following research questions: (1) Does priming reveal a psycholinguistic process that could underlie historical language change and, if so, how? (2) Do differences in priming effects between ages of bilingual speakers account for developmental differences that could be relevant for historical language change? The first question addresses key feature 1 of the Research Unit "Structuring the Input in Language Acquisition, Processing, and Change" (SILPAC), while the second question addresses key feature 2. These questions will be examined with respect to different factors modulating the use of argument structure information (key feature 3), with the goal of advancing experimental processes and models to understand change (key feature 4).