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Is there a closure penalty? Cohesive network structures, diversity, and gender inequalities in career advancement

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  • Lutter, Mark

Abstract

That social capital matters is an established fact in the social sciences. How different forms of social capital affect gender disadvantages in career advancement is less clear, however. Qualitative research suggests that women face disadvantages in project-based labor markets where recruitment practices are based on informal and personal networks. Focusing on a project-based type of labor market, namely the U.S. film industry, this study argues that women suffer from social closure and face severe career disadvantages when collaborating in cohesive teams. At the same time, gender disadvantages are reduced for women who build social capital in open networks with a higher degree of diversity and information flow. I test and demonstrate these assumptions using a large-scale longitudinal dataset containing full career profiles of more than 1.2 million performances by 101,090 film actors in 483,949 feature film productions between the years 1900-2010. In particular, I analyze career survival models and interaction effects between gender and different measures of social capital and information openness. The findings reveal that female actors have a higher risk of career failure than their male colleagues when affiliated in cohesive networks, but have better survival chances when embedded in open and diverse structures. This study contributes to the understanding of how and what type of social capital can be either a beneficial resource for otherwise disadvantaged groups or a constraining mechanism that intensifies gender differences in career advancement.

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  • Lutter, Mark, 2013. "Is there a closure penalty? Cohesive network structures, diversity, and gender inequalities in career advancement," MPIfG Discussion Paper 13/9, Max Planck Institute for the Study of Societies.
  • Handle: RePEc:zbw:mpifgd:139
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    1. Andersen, Kristina Vaarst, 2013. "The problem of embeddedness revisited: Collaboration and market types," Research Policy, Elsevier, vol. 42(1), pages 139-148.
    2. Carter, David B. & Signorino, Curtis S., 2010. "Back to the Future: Modeling Time Dependence in Binary Data," Political Analysis, Cambridge University Press, vol. 18(03), pages 271-292, June.
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    Cited by:

    1. Ilse Lindenlaub & Anja Prummer, 2016. "Gender, Social Networks and Peformance," Working Papers 807, Queen Mary University of London, School of Economics and Finance.

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