Future-time Reference in Australian English

The present paper investigates the be going to vs. will/shall alternation in Australian English. By drawing on quantitative data collected through the Corpus of Global Web-Based English (GloWbE), random forests techniques and conditional decision trees are applied to assess the importance of selected independent variables and to visualize how contexts of specialization are set apart based on the interaction of multiple factors. The results reveal that the predictors traditionally thought to influence the probabilistic grammar of the be going to vs. will/shall alternation in other L1 varieties of English only partly account for the variation observed in Australian English. The model reports better predictive results for will/shall and shows that text- specific preferences play a significant role in this alternation. Additionally, Proximity and Sentence Type emerge as the strongest predictors, indicating that grammaticalization processes affect different grammatical categories and are closely tied with semantics as well as syntactic complexity.