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This paper seeks to address the relationship between social capital and perceived social origin in contemporary Austria. While the concept of social capital has been widely adopted in social sciences, so far research on the (pre)structured shape of social capital by social origin is scarce. Our aim is to close this gap. Therefore, we use the network-as-capital approach by following the “position generator” and apply latent class analysis (LCA) and path modelling on the basis of the 2018 Austrian Social Survey. The dataset comprises a representative sample of the Austrian residential population aged 18 and older. Our findings show that the diversity of social capital, and access to networks of people in more highly ranked positions is strongly influenced by one’s social background. The higher respondents assess their social origin, the greater the probability of being in this type of network. Furthermore, education and occupation have effects on membership in a class-specific network.
The gendered division of occupations is a persistent characteristic of the Austrian labour market. Furthermore, we can observe more flexible employment biographies, where sequential employment episodes and occupational transitions become an important part. On this account, the article argues that both gender inequalities and labour market movements need to be examined simultaneously. The authors therefore analyse gender-(un)typed horizontal occupational transitions and their influence on the vertical positioning, based on the Austrian Micro Census (2008–2018). The results reveal that gender-typed occupational transitions are regaining relevance and that the gender effect is reversing in that women increasingly leave gender-untyped occupations. The findings also demonstrate that this gender-typed horizontal movement yields a significant decline in occupational status for women, which even increases when women become mothers. Based on their models the authors find no negative effects for fathers.
This paper seeks to address the relationship between social capital and perceived social origin in contemporary Austria. While the concept of social capital has been widely adopted in social sciences, so far research on the (pre)structured shape of social capital by social origin is scarce. Our aim is to close this gap. Therefore, we use the network-as-capital approach by following the “position generator” and apply latent class analysis (LCA) and path modelling on the basis of the 2018 Austrian Social Survey. The dataset comprises a representative sample of the Austrian residential population aged 18 and older. Our findings show that the diversity of social capital, and access to networks of people in more highly ranked positions is strongly influenced by one’s social background. The higher respondents assess their social origin, the greater the probability of being in this type of network. Furthermore, education and occupation have effects on membership in a class-specific network.