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

本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。我们特别关注双语儿童和成人是否会因为他们所经历的输入而受到影响而改变语法模式。我们认为这是历史上可能发生的由接触引起的跨语言影响的一种模式，从而导致语言随着时间的推移而永久改变。因此，这个项目探索了在个体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法，重点研究了两种结构：补语交替和动小品结构交替。为了回答以下研究问题，我们研究了儿童和成人德语-英语和法语-英语双语者的跨语言影响的潜力：(1)启动是否揭示了一个可能成为历史语言变化基础的心理语言过程，如果是，是如何揭示的？(2)双语者年龄间启动效应的差异能否解释与历史语言变化相关的发展差异？第一个问题解决了“构建语言习得、处理和变化中的输入”（SILPAC）研究单元的关键特征1，而第二个问题解决了关键特征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，目标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).