Abangma, Samson Negbo; (1992) Empty categories in Denya. Doctoral thesis (Ph.D), UCL (University College London).

Preview

Text Empty_categories_in_Denya.pdf Download (6MB) | Preview

Abstract

This work presents a study of empty categories (ECs) in Denya, an Ekoid Bantu language spoken mainly in Cameroon. It is undertaken within the framework of Government Binding (GB) Theory. The study shows that the current theories of GB based mainly on the analysis of English, some European languages and Chinese/Japanese, can also be applied to Denya, an African language. The study starts by accepting the four types of ECs established by Chomsky - PRO, pro, NP-trace, wh-trace. In addition, the study looks at parasitic gaps, a phenomenon receiving considerable attention in the current literature. The thesis comprises six main chapters and a conclusion. Chapter 1 entitled ''Preliminaries" is basically introductory and deals with the goal, the scope and limitations of the work. It also includes a brief account of GB. Chapter 2 looks at PRO, the pronominal anaphor. Chapter 3 examines pro. the pure pronominal [+p, - a] EC found only in null subject languages. In the following chapter, NP-trace receives attention. In the fifth chapter our interest is taken by the wh-trace, while the sixth chapter examines the phenomenon of parasitic gaps. The work terminates in chapter 7 with a brief conclusion. Here the various threads of the discussion in the preceding chapters are drawn together, the importance of the study is suggested and indications of areas of further research are made. It is worth noting that this work makes, in a modest way, a contribution to our understanding of the principles of Universal Grammar as suggested in Chomsky (1981, 1982, 1986, 1986b). We have been able to show the extent to which the features of ECs in the language can be established by a limited number of parametric settings.

Download activity - last month

Export as XMLJSONCSV

Download activity - last 12 months

Export as JSONXMLCSV

Downloads by country - last 12 months

Export as CSVJSONXML

Archive Staff Only

View Item