Modeling the Bilingual Phonological Idiolect Through a Translanguaging Lens
Year: 2025
Type: article
Study design: Observational Study
Abstract: Purpose: The dual-systems hypothesis is a theoretical framework that aims to describe the structuring of the bilingual linguistic system as two separated, differentiated systems with points of contact. However, the emergence of translanguaging has shifted the perspective of how scholars in the study of bilingualism understand language representation. Using translanguaging to advance toward a bilingual phonological idiolect, building upon a dual-systems model, the purpose of this study was to develop a representative theoretical model that more deeply reflects bilingual phonological representation. Method: Phonetic inventories from 40 typically developing bilingual Spanish-English–speaking children ( x¯ age = 5;2 [years;months]) were analyzed, and frequency of substitutes for a given target was calculated. Frequency data were then transformed into contingency tables that underwent social network analysis. Networks of phones were identified as evidence of a unitary phonological idiolect. Results: Network analysis yielded plots illuminating the network of the bilingual phonological idiolect as well as the systematicity of these substitutions. Metrics of network analysis yielded ways in which this network can be used to anticipate and predict speech sound substitutions that are frequent for nonimpaired speech in bilingual preschoolers. Conclusions: Researchers concluded that network interactions reveal a more interactive and complex network that could not be parsed into two phonological systems. Identification of networks of related speech sounds, and frequency and directionality of substitution patterns, could aid in the prevention of misdiagnosis of speech sound disorders in bilingual children.
Authors: Brandon Garivaldo, Leah Fabiano
Institution: University of Pittsburgh
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
Award: G4070087437
OpenAlex ID: W4415393406