This collection brings together the authors' previous research with new work on the Register-Functional (RF) approach to grammatical complexity, offering a unified theoretical account for its further study. The book traces the development of the RF approach from its foundations in two major research strands of linguistics: the study of sociolinguistic variation and the text-linguistic study of register variation. Building on this foundation, the authors demonstrate the RF framework at work across a series of corpus-based research studies focused specifically on grammatical complexity in English. The volume highlights early work exploring patterns of grammatical complexity in present-day spoken and written registers as well as subsequent studies which extend this research to historical patterns of register variation and the application of RF research to the study of writing development for L1 and L2 English university students. Taken together, along with the addition of introductory chapters connecting the different studies, the volume offers readers with a comprehensive resource to better understand the RF approach to grammatical complexity and its implications for future research. The volume will appeal to students and scholars with research interests in either descriptive linguistics or applied linguistics, especially those interested in grammatical complexity and empirical, corpus-based approaches.

This book offers original corpus research in a range of workplace contexts including office-based settings, call center interactions and healthcare communication. Chapters in this edited volume bring together leading scholars in the field of corpus analysis in workplace discourse and include data from multiple corpora. Employing a range of qualitative and quantitative analytic approaches including Conversation Analysis, Linguistic Profiling and Register Analysis, the book introduces unique specialized corpus data in the areas of Augmentative and Alternative Communication, nursing, and cross-cultural communication, among others.