Recent work within the language sciences, particularly bilingualism, has sought new methods to evaluate and characterize how people differentially use language across different communicative contexts. These differences have thus far been linked to changes in cognitive control strategy, reading behavior, and brain organization. Here, we approach this issue using a novel application of Network Science to map the conversational topics that Montréal bilinguals discuss across communicative contexts (e.g., work, home, family, school, social), in their dominant vs. nondominant language. Our results demonstrate that all communicative contexts display a unique pattern in which conversational topics are discussed, but only a few communicative contexts (work and social) display a unique pattern of how many languages are used to discuss particular topics. We also demonstrate that the dominant language has greater network size, strength, and density than the non-dominant language, suggesting that more topics are used in a wider variety of contexts in this language. Lastly, using community detection to thematically group the topics in each language, we find evidence of greater specificity in the non-dominant language than the dominant language. We contend that Network Science is a valuable tool for representing complex information, such as individual differences in bilingual language use, in a rich and granular manner, that may be used to better understand brain and behavior.
Human cognition occurs within social contexts, and nowhere is this more evident than language behavior. Regularly using multiple languages is a globally ubiquitous individual experience that is shaped by social environmental forces, ranging from interpersonal interactions to ambient language exposure. Here, we develop a Systems Framework of Bilingualism, where embedded layers of individual, interpersonal, and ecological sociolinguistic factors jointly predict people's language behavior. Of note, we quantify interpersonal and ecological language dynamics through the novel applications of language-tagged social network analysis and geospatial demographic analysis among 106 English-French bilingual adults in Montréal, Canada. Consistent with a Systems view, we found that people's individual language behavior, on a global level (i.e., overall language use), was jointly predicted by the language characteristics of their interpersonal social networks and the ambient linguistic patterns of their residential neighborhood environments, whereas more granular aspects of language behavior (i.e., word-level proficiency) was mainly driven by local, interpersonal social networks. Together, this work offers a novel theoretical framework, bolstered by innovative analytic techniques to quantify complex social information and empower more holistic assessments of multifaceted human behaviors and cognition, like language.
Human cognition occurs within social contexts, and nowhere is this more evident than language behavior. Regularly using multiple languages is a globally ubiquitous, individual experience that is shaped by social environmental forces, ranging from interpersonal interactions to ambient language exposure. Here, we develop a Systems Framework of Bilingualism, where embedded layers of individual, interpersonal, and ecological sociolinguistic factors jointly predict people’s language behavior. Of note, we quantify interpersonal and ecological language dynamics through the novel applications of language-tagged social network analysis and geospatial demographic analysis among 106 English-French bilingual adults in Montréal, Canada. Consistent with a Systems view, we found that people’s individual language behavior, on a global level (i.e., overall language use), was jointly predicted by the language characteristics of their interpersonal social networks and the ambient linguistic patterns of their residential neighborhood environments, whereas more granular aspects of language behavior (i.e., word-level proficiency) was mainly driven by local, interpersonal social networks. Together, this work offers a novel theoretical framework, bolstered by innovative analytic techniques to quantify complex social information and empower more holistic assessments of multifaceted human behaviors and cognition, like language.
Recent work within the language sciences, particularly bilingualism, has sought new methods to evaluate and characterize how people differentially use language across different communicative contexts. These differences have thus far been linked to changes in cognitive control strategy, reading behavior, and brain organization. Here, we approach this issue using a novel application of Network Science to map the conversational topics that Montréal bilinguals discuss across communicative contexts (e.g., work, home, family, school, social), in their dominant vs. non-dominant language. Our results demonstrate that all communicative contexts display a unique pattern in which conversational topics are discussed, but only a few communicative contexts (work and social) display a unique pattern of how many languages are used to discuss particular topics. We also demonstrate that the dominant language has greater network size, strength, and density than the non-dominant language, suggesting that more topics are used in a wider variety of contexts in this language. Lastly, using community detection to thematically group the topics in each language, we find evidence of greater specificity in the non-dominant language than the dominant language. We contend that Network Science is a valuable tool for representing complex information, such as individual differences in bilingual language use, in a rich and granular manner, that may be used to better understand brain and behavior.
Background: Significant disparities in utilization of mental health services exist among immigrant and Canadian-born populations. These gaps may be associated with a ‘double stigma’ – stigma related to being from a racialized background exacerbated by mental health stigma. Immigrant young adults may be particularly susceptible to this phenomenon, given developmental and social transitions from adolescence to adulthood. Aims: To investigate the joint effects of racial microaggression and mental health stigma on mental health and service use among first-generation immigrant and Canadian-born university students. Method: We conducted an online cross-sectional study among first-generation immigrant and Canadian-born university students (N = 1,280, Mage = 19.10, SD = 1.50). Results: Despite no differences in anxiety or depression symptoms, first-generation (foreign-born) immigrants were less likely to have received therapy and to have taken medication for mental health issues compared to Canadian-born participants. First-generation immigrants also reported experiencing higher levels of racial microaggression and stigma toward service use. Results suggest the presence of a double stigma, mental health stigma and racial microaggression, each explained significant additional variance in symptoms of anxiety and depression and medication use. No effects of double stigma for therapy use were found – while higher mental health stigma predicted lower use of therapy, racial microaggression did not predict unique variance in therapy use. Conclusions: Our findings highlight the joint effects of racial microaggression and stigma toward mental health and service as barriers to help-seeking among immigrant young adults. Mental health intervention and outreach programmes should target overt and covert forms of racial discrimination while incorporating culturally sensitive anti-stigma approaches to help reduce disparities in mental health service use among immigrants in Canada.
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