Abstract
AbstractThis study investigates the effect of socioeconomic status (SES) as a proxy for input quality, in predicting language proficiency. Different operationalizations of SES are compared, including simple measures (parental education and parental occupation) and complex measures combining two dimensions (among parental education, parental occupation, and deprivation risk). All significantly predict overall English proficiency scores in a diverse group of 5- to 7-year-olds acquiring English and another language. The most informative SES measure in that respect is shown to be a complex measure combining parental education and parental occupation. That measure is used in a second set of analyses showing that different aspects of language are affected differently by variations in SES and in language exposure.
Highlights
It has become uncontroversial that bilingual children’s proficiency in each language is influenced by the amount of exposure they experience in each language (Paradis, 2017; Unsworth, 2017)
I adopt a broad definition of input quality, taking into account any aspect of the linguistic environment that goes beyond input quantity as it is traditionally operationalized
The first part of the paper investigated the interaction between cumulative English exposure and Socioeconomic status (SES) as predictors of proficiency in the school language in a socioeconomically diverse group of 5- to 7-year-old bilinguals schooled in English
Summary
It has become uncontroversial that bilingual children’s proficiency in each language is influenced by the amount of exposure they experience in each language (Paradis, 2017; Unsworth, 2017). I adopt a broad definition of input quality, taking into account any aspect of the linguistic environment that goes beyond input quantity as it is traditionally operationalized (i.e., as “time spent with interlocutors X, Y, Z,” which only measures the opportunity for language interaction with those interlocutors, whether it is realized or not) Under this broad definition, input quality can include quantitative aspects of language exposure, such as the actual amount of linguistic interaction (e.g., caregivers’ verbal responsiveness; Hoff, 2006), density of language use (e.g., lexical or clausal density; Huttenlocher, Haight, Bryk, Seltzer, & Lyons, 1991), and other distributional properties of the input. In their review, Perkins, Finegood, and Swain (2013) highlight two potentially explanatory dimensions, stemming from the well-documented association between low SES and (a) high chronic stress (which impacts the cognitive control system underpinning language development) as well as (b) lower quality of the home environment in terms of literacy practices, parental language, and parenting styles (all of which have an impact on children’s language development)
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