A network's gender composition and communication pattern predict women's leadership success

Yang Yang, Nitesh V. Chawla, Brian Uzzi*

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Many leaders today do not rise through the ranks but are recruited directly out of graduate programs into leadership positions. We use a quasi-experiment and instrumental-variable regression to understand the link between students' graduate school social networks and placement into leadership positions of varying levels of authority. Our data measure students' personal characteristics and academic performance, as well as their social network information drawn from 4.5 million email correspondences among hundreds of students who were placed directly into leadership positions. After controlling for students' personal characteristics, work experience, and academic performance, we find that students' social networks strongly predict placement into leadership positions. For males, the higher a male student's centrality in the school-wide network, the higher his leadership-job placement will be. Men with network centrality in the top quartile have an expected job placement level that is 1.5 times greater than men in the bottom quartile of centrality. While centrality also predicts women's placement, high-placing women students have one thing more: an inner circle of predominantly female contacts who are connected to many nonoverlapping third-party contacts. Women with a network centrality in the top quartile and a female-dominated inner circle have an expected job placement level that is 2.5 times greater than women with low centrality and a male-dominated inner circle. Women who have networks that resemble those of high-placing men are low-placing, despite having leadership qualifications comparable to high-placing women.

Original languageEnglish (US)
Pages (from-to)2033-2038
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume116
Issue number6
DOIs
StatePublished - Feb 5 2019

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Keywords

  • Computational social science
  • Gender inequality
  • Leadership
  • STEM
  • Social network

ASJC Scopus subject areas

  • General

Cite this

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A network's gender composition and communication pattern predict women's leadership success. / Yang, Yang; Chawla, Nitesh V.; Uzzi, Brian.

In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 116, No. 6, 05.02.2019, p. 2033-2038.

Research output: Contribution to journalArticle

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