Abstract

This study uses a novel approach to describe modern English academic texts in terms of the amount and distribution of syntactic subordination, coordination and phrasal structures. Inconsistent results have been reported in previous scholarship regarding the trajectory of syntactic complexification based on English language backgrounds and linguistic proficiency of writers. For the first time, a combination of two predictive statistical modelling methods of mixed-effects modelling and supervised machine learning modelling with random forest is used to examine the extent to which the type, amount, and distribution of these syntactic structures can be attributed to a text-intrinsic feature (sub-genres or rhetorical sections of academic register) and a text-extrinsic factor (English language background based on academic context) in a corpus of master’s dissertations. To revisit the theories of English L1 vs. L2 texts, strong predictors of syntactic complexity across academic writings of EFL, ESL, and English L1 postgraduate students were identified. The findings show that EFL texts are dominantly subordinate in nature, English L1’s dominantly phrasal, and the ESL dissertations exhibited similar amounts of subordination and phrasal structures. Distinct syntactic structures also characterise rhetorical sections: abstracts are predominantly phrasal, literature reviews distinctly subordinate, and conclusion sections have noticeable amounts of verb phrases.

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