Effects of Spatial Characteristics on Non-Standard Employment for Canada's Immigrant Population

Using microdata from Statistics Canada's Labour Force Survey (LFS) and Population Census, this paper explores how spatial characteristics are correlated with temporary employment outcomes for Canada's immigrant population. Results from ordinary least square regression models suggest that census metropolitan areas and census agglomerations (CMAs/CAs) characterized by a high share of racialized immigrants, immigrants in low-income, young, aged immigrants, unemployed immigrants, and immigrants employed in health and service occupations were positively associated with an increase in temporary employment for immigrants. Furthermore, findings from principal component regression models revealed that a combination of spatial characteristics, namely CMAs/CAs characterized by both a high share of unemployed immigrants and immigrants in poverty, had a greater likelihood of immigrants being employed temporarily. The significance of this study lies in the spatial conceptualization of temporary employment for immigrants that could better inform spatially targeted employment policies, especially in the wake of the structural shift in the nature of work brought about by the COVID-19 pandemic.

Gender, Space, and Precarious Employment in Canada

This study aims to examine how gendered precariousness is spatially patterned across Canada's landscape using Statistics Canada's Labour Force Survey. We compare gender differences in distinct precarious forms of employment (PFEs) across a range of geographies, including national, provincial, census metropolitan areas, and urban/rural areas. We find that distinct spatial patterns and degree of gendered precariousness were evident within and across geographic spaces. Logit models further confirmed the robustness of gender differences in PFEs across space, revealing that PFEs were associated with gender, immigration status, age, type of economic family, education, income, and occupation. This study has implications for further understanding the causal factors at play in producing these uneven economic geographies. In terms of policy recommendations, this study calls for greater gender equity in social safety net policies, especially in the wake of the labor market shocks brought by the COVID‐19 pandemic. [ABSTRACT FROM AUTHOR] Copyright of Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)