Micro to macro: Modelling language variation across time

Language evolution and biological evolution have been courting each other since Darwin. Darwin was interested in language evolution because languages change rapidly enough to be visible, unlike biological evolution. Linguistics has borrowed methods from biology to understand how languages change on a macro (phylogenetics) and, more recently, a micro (population genetics) level. The mapping from the micro to macro is a fundamental puzzle in biology for understanding how speciation works. For linguistics, it is about how population-level language use leads to new languages i.e., linguistic diversification.

This talk steps through a number of recent developments in language evolution which bridge these identified gaps. I introduce BayesVarbrul, developed by Hua (2022), which models the change in the frequency of linguistic variants across different generations and regions, and the effect of social factors on the uptake and loss of these variants across space and time. It is designed for datasets with multiple variables and multiple speakers from different generations and speech communities. An early version of BayesVarbrul was first applied to a situation of language change in northern Australia where an intergenerational shift from Gurindji to Gurindji Kriol is underway. But the Gurindji Kriol dataset did not offer the possibility of exploring both time and space because the data was only collected in one community and therefore lacks a regional dimension. This paper introduces a new dataset of Shawi speakers from Peru which has the necessary regional dimension, as well as generational dimension. We use this dataset to model the emergence of a new dialect of Shawi across 168 speakers from different ages and different regions, paying particular attention to the variation in word order at an individual speaker and regional level. I then return to the Gurindji Kriol dataset describing an experimental approach which has allowed us to create a metric for the (non)-association of social salience (Hua et al 2026) and its effect on the flow of linguistic variants over time (Meakins et al submitted).