文章基本信息

标题：Lone Mothers' Employment Trajectories: A Longitudinal Mixed-method Study
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作者：Emanuela Struffolino ; Laura Bernardi ; Ornella Larenza 等
期刊名称：Comparative Population Studies
印刷版ISSN：1869-8980
电子版ISSN：1869-8999
出版年度：2020
卷号：45
页码：265-298
DOI：10.12765/CPoS-2020-14
出版社：Federal Institute for Population Research
摘要：Using a mixed-method design, this study explores the heterogeneity in employment trajectories before and after the transition to lone parenthood in Switzerland. First, we perform sequence and cluster analysis on data from the Swiss Household panel to identify typical employment trajectories around the transition to lone parenthood, and then estimate their association with individual and household characteristics (N=462). Finally, we contrast these results with findings from a content analysis of narrative interviews with lone mothers residing in Switzerland (N=38), focusing on values and norms concerning work and care. We identify five employment patterns characterized by either an increase in labor supply (especially for those with more/older children) or by stability in or outside the labor market (for highly educated or younger mothers respectively). The analyses of the interviews provide insights on how employment opportunities and decisions differ by entry mode into lone parenthood, the post-separation relationship with the children’s father, and the ability to mobilize individual, social and institutional resources. The heterogeneity of employment trajectories calls for more attention to within-group differences rather than focusing exclusively on the divide between lone and coupled mothers. By identifying the multiplicity of factors shaping lone mothers’ decisions on their labor market participation, this work feeds into the literature suggesting that effective policies encouraging lone mothers’ labor-market participation should consider: (i) their normative priorities when facing work and care trade-offs, and (ii) the availability of informal and formal support.
关键词：Employment; Lone Parenthood; Mixed-method; Sequence analysis; Switzerland