Linguistic Typology and Austronesian Syntax
Associate Professor I Wayan Arka (Australian National University)
Professor Ketut Artawa (Udayana University)
Dr. Sonja Riesberg (University of Cologne)
9-14 September 2019
This course is an introduction to the fundamental concepts of (morpho)syntax in linguistics and linguistic typology — the study of worldwide distribution of linguistic diversity by investigating the patterns in languages’ similarities and differences. We will discuss the rich variety of syntactic structures found in the Austronesian world. Austronesian is the world’s largest language family in terms of geographical spread, spanning more than half the globe: from Madagascar to Easter Island, and from Taiwan to New Zealand. This vast and diverse language family is also one of the best documented. It includes both major world languages with millions of speakers, like Indonesian and Tagalog, and tiny Oceanic languages spoken on a remote island with only a couple of hundred speakers.
During the course you will be exposed to the aims, methods, and research results of typology within the domains of (morpho-)syntax. The course will also offer glimpses of recent developments in how linguistic typology interacts with other types of linguistic pursuits, such as descriptive and documentary linguistics, historical linguistics and theoretical linguistics.
The sessions will be organised around comparative-typological themes, providing the foundation for analysis of the similarities and differences among different subgroups of Austronesian languages. Upon successful completion of this course, you should be familiar with the salient typological profiles of the Austronesian languages, and you should be able to do typological research on relevant morphosyntactic topics, including presentation and justification of your analyses and results.
This course is of international standard, and can be taken for credit. It is an intermediate level course of linguistics, equivalent to the ANU’s 2000-level course (6 units). A detailed course outline and preliminary reading will be posted soon.
Chapter 1 of Blust, Robert. 2013. The Austronesian Languages (the revised edition). Canberra: Asia-Pacific Linguistics.
Chapter 1 of Moravcsik, Edith. 2013. Introducing Language Typology. Cambridge: Cambridge University Press.
Introduction to R
Gede Primahadi Wijaya Rajeg, PhD (Udayana University)
17 September 2019
In this two-hour demo-talk*, I will briefly discuss (i) why R is a big deal for 21st century research, and then (ii) showcasing a number of its state-of-the-art features in relation to a unified data science workflow, such as working with tabular and textual data, data visualisation, as well as generating reproducible documents from R. The talk seeks to generate concrete impression regarding R’s ability for attendees who are interested in starting to learn R.
Baayen, R. Harald. 2008. Analyzing linguistic data: A practical introduction to statistics using R. Cambridge, UK ; New York: Cambridge University Press. doi:10.1017/CBO9780511801686. (Open-access, draft-version is available here)
Desagulier, Guillaume. 2017. Corpus Linguistics and Statistics with R: Introduction to Quantitative Methods in Linguistics. Cham: Springer International Publishing. doi:10.1007/978-3-319-64572-8 (27 January, 2018).
Gries, Stefan Th. 2013. Statistics for linguistics with R: A practical introduction. 2nd edn. Berlin: Mouton de Gruyter.
Gries, Stefan Th. 2017. Quantitative corpus linguistics with R: A practical introduction. Second edition. New York: Routledge.
Levshina, Natalia. 2015. How to do Linguistics with R: Data exploration and statistical analysis. John Benjamins Publishing Company. doi:10.1075/z.195.
R Core Team. 2019. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Rajeg, Gede Primahadi Wijaya, Karlina Denistia & I Made Rajeg. 2018. Working with a linguistic corpus using R: An introductory note with Indonesian negating construction. Linguistik Indonesia36(1). 1–36. doi:10.26499/li.v36i1.71. (Repository for R codes and details about the data are available at https://doi.org/10.4225/03/5a7ee2ac84303)