Describing languages, linguists, and their contribution: Challenges and opportunities in working with data

It is exciting to be able to identify patterns across hundreds or thousands of languages or trends across the history of linguistics. But how do we get there? In this talk I will discuss some of the challenges and opportunities in working with data related to linguistic typology and the historiography of linguistics, based on two case studies.

In the first, I will present joint work with Harald Hammarström (Uppsala University) showing how the DReaM corpus, which includes over 15,000 grammars and grammar sketches (Virk et al. 2020), can be used to trace the transmission of linguistic concepts such as classifier, noun incorporation, and polysynthesis. In the second, I will reconstruct a late 19th-century debate on polysynthesis against the personal background of two scholars — D.G. Brinton and J.N.B. Hewitt — drawing on published papers and archival correspondence. The two approaches, corpus-based/quantitative and archival/qualitative, allow us to appreciate both their descriptive and theoretical benefits and the methodological challenges they pose.

It is therefore important to take a step back and, inverting Leonard Bloomfield’s caution — “don’t take your guests in the kitchen” (as cited in Hockett 1966: 67) — to make the steps behind the results visible, in order to share practices and find better ways to communicate our research beyond our own field.

References:

Hockett, Charles F. 1966. What Algonquian is really like. International Journal of American Linguistics 32(1). 59–73. https://doi.org/10.1086/464880.

Virk, Shafqat Mumtaz, Harald Hammarström, Markus Forsberg & Søren Wichmann. 2020. The DReaM corpus: A multilingual annotated corpus of grammars for the world’s languages. In Nicoletta Calzolari et al. (eds.), Proceedings of the Twelfth Language Resources and Evaluation Conference, 878–884. Marseille: European Language Resources Association.

Zoom: https://us06web.zoom.us/j/85250575838?pwd=M21okObuBY0UjWZgED4b18ms2O4JXr.1#success.