Methods: We US American Community Survey data collected from 2012 to 2016. The sample consists of working-age immigrants (25 to 54 years old) living in Western New York who are not enrolled in school (608 men and 692 women). The dependent variable is dichotomous (currently employed or not). Independent variables are language-related: individual-level English proficiency (0 for speaking English only, 1 for very well, 2 for well, 3 for not well, and 4 for not at all); community language resource (the percentage of adults who speak English very well among those speaking the same language as an immigrant in the Public Use Microdata Area of residency); and the interaction between these two language variables. We use logit regressions and control for demographics, household characteristics, human capital, immigration-related factors, and environmental factors. We run separate regression analyses by sex.
Results: Analyses show gender differences in employment status: 83% of immigrant men are employed while 58% of women are. Regression analyses show different relationships among individual English proficiency, CLR, and employment status. The chance of being employed among immigrant men with LEP significantly increases as the level of community language resource increases. The predicted probability of being employed jumps from 37% to 83% among immigrant men who cannot speak English at all as the level of CLR increases from 10% to 90%. The interaction term between individual English proficiency and CLR is not statistically significant, suggesting that community language resources do not facilitate employment among immigrant women with LEP.
Conclusions and Implications: This study indicates the important role of community language resources in immigrant men’s employment. Findings suggest that community resources may have distinct impacts by sex. Results call for policy and community interventions that mobilize language resources for immigrants with limited English proficiency for their long-term economic security and development. Findings challenge a gender-blind employment policy toward immigrants.