At the end of this course you are able to read, evaluate and comment upon scientific articles within the domain of linguistic universals and diversity. You can understand linguistic analyses within this domain, compare them and apply them to new data. You can formulate candidates for linguistic universals in a specific area and test them on diverse languages of the world. You can read grammars written by language experts and fieldworkers and encode relevant information in an open-access typological database using the cross-linguistic data format (CLDF).
|
|
Language gives us a special window on human diversity and universality. Systematic comparison of structural and semantic properties of different languages has various aims:
- discovering the extent and the limits of linguistic diversity;
- discovering the underlying principles by which variation among languages is constrained;
- discovering the origins of diversity;
- discovering the distribution of the linguistic patterns in time and space.
Each year this course focuses on a specific topic, within which linguistic universals and diversity are examined. The topic for 2021 is differential argument marking. It is a very wide-spread phenomenon across languages of the world, which has attracted the attention of numerous researchers. We examine the following questions:
- What kind of semantic, pragmatic, lexical and morphosyntactic features are responsible for differential marking?
- Are there universal effects associated with diverse referential scales, such as animacy hierarchy?
- How can we explain these patterns from a cognitive and communicative perspective?
- Are there geographic and genealogical biases in the spread of differential marking?
- How does differential object marking emerge and develop in time?
|
 |
|
|
|
In addition to an oral presentation, the result of this course is a paper, which consists of three parts:
1) Linguistic universals related to differential marking;
2) Data from two different languages, organized in a specific format;
3) Your conclusion whether the data support your universals or not.
All these issues will be discussed regularly in the class, step by step.
|
|
|