Suresh Rishabh

RTG PhD student, member since 2024

Project "Null subjects diachronically and typologically "

In many languages it is possible to construct grammatical utterances where one or more arguments in a clause are silent or null, with null subjects being perhaps the most common. It has moreover been observed that prototypical null-subject languages like Spanish or Italian display rich verbal agreement, and this has been argued to be what licenses the null subjects. These accounts assume that languages where direct and indirect objects can also be left unexpressed such as many East and South Asian languages, so-called 'discourse pro-drop languages', use a different mechanism to license their null arguments, as they tend to have poor or entirely non-existent verbal agreement. However, the realization that languages can also belong somewhere between the full null-subject languages and the discourse pro-drop ones (by for example only allowing some kinds of subjects to be null) has complicated the picture. This project will therefore look into what the other factors may be that make null subjects possible, and more generally, whether there is an alternative account that can capture the variation we find across languages in the availability of null arguments.

Background and research interests:

I completed my BA in Liberal Arts and Sciences from University College Utrecht in 2022, majoring in Mathematics and Linguistics and with a thesis in analytic number theory. I then completed an MA in Linguistics at Utrecht University in 2024. My focus was on phenomena in the interface between syntax and semantics in the verbal domain, and my thesis was on the structure of the Tamil clausal spine based on insight from asymmetries in the expression of temporality in affirmative and negative clauses. Aside from null subjects, I remain passionate about the syntax-semantics of tense, aspect, modality, and negation, particularly in Dravidian and Indo-Aryan. Methodologically, I am interested in the use of corpus-based as well as offline experimental methods and the large datasets they generate, particularly in the context of research into understudied languages.