TY - JOUR
T1 - Differential Social Network Effects on Scholarly Productivity
T2 - An Intersectional Analysis
AU - Gaughan, Monica
AU - Melkers, Julia
AU - Welch, Eric
N1 - Funding Information:
We thank the National Science Foundation for its support of this work, our NSF program officer Janice Earle for her guidance and support, the reviewers for their useful feedback, and the academic scientists who generously provided their time and input to this study.
Funding Information:
While low representation is a critical issue, there is also evidence of significant barriers to career development and advancement for URM groups, who hold fewer tenured and full professor positions (Perna 2001) and on average have lower salaries, fewer publications, and less external funding other scientists (NSF 2015). Evidence of discrimination in academic environments suggests barriers to participation in academic production and career advancement (Turner 2002). These barriers may also explain the significant and dramatic racial disparities in National Institutes of Health (NIH) grant success (Ginther et al. 2011). Women as a group have made progress in representation on university faculty in some Science, Technology, Engineering, and Mathematics (STEM) disciplines, but they continue to be underrepresented in all of the STEM disciplines (NSF 2015). Studies continue to be limited by an inability to study important gender, race, and ethnicity interactions because of small cell sizes (Leggon 2006). Finally, while Asian faculties are not included in the National Science Foundation definition of underrepresented minorities, evidence of disadvantage for Asian women has received attention (Malcom and Malcom 2011; Matchett 2013). In this research, we bring gender, race, and ethnicity together in an intersectional analysis of the social network determinants of academic productivity in academic science and engineering.
Funding Information:
Data presented in this article come from the National Science Funded Project: “Netwise II: Empirical Research: Breaking through the Reputational Ceiling: Professional Networks as a Determinant of Advancement, Mobility, and Career Outcomes for Women and Minorities in STEM,” a project funded by the National Science Foundation (grant no. DRL-0910191; coprincipal investigators: Julia Melk-ers, Eric Welch, and Monica Gaughan and Program Officer Janice Earle).
Publisher Copyright:
© 2017, © The Author(s) 2017.
PY - 2018/5/1
Y1 - 2018/5/1
N2 - Academic productivity is realized through resources obtained from professional networks in which scientists are embedded. Using a national survey of academic faculty in Science, Technology, Engineering, and Mathematics (STEM) fields across multiple institution types, we examine how the structure of professional networks affects scholarly productivity and how those effects may differ by race, ethnicity, and gender. We find that network size masks important differences in composition. Using negative binomial regression, we find that both the size and composition of professional networks affect scientific productivity, but bigger is not always better. We find that instrumental networks increase scholarly productivity, while advice networks reduce it. There are important interactive effects that are masked by modeling only direct effects. We find that white men are especially advantaged by instrumental networks, and women are especially advantaged by advice networks.
AB - Academic productivity is realized through resources obtained from professional networks in which scientists are embedded. Using a national survey of academic faculty in Science, Technology, Engineering, and Mathematics (STEM) fields across multiple institution types, we examine how the structure of professional networks affects scholarly productivity and how those effects may differ by race, ethnicity, and gender. We find that network size masks important differences in composition. Using negative binomial regression, we find that both the size and composition of professional networks affect scientific productivity, but bigger is not always better. We find that instrumental networks increase scholarly productivity, while advice networks reduce it. There are important interactive effects that are masked by modeling only direct effects. We find that white men are especially advantaged by instrumental networks, and women are especially advantaged by advice networks.
KW - academic productivity
KW - advice networks
KW - gender
KW - social networks
KW - underrepresented minorities
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U2 - 10.1177/0162243917735900
DO - 10.1177/0162243917735900
M3 - Article
AN - SCOPUS:85044821494
SN - 0162-2439
VL - 43
SP - 570
EP - 599
JO - Science Technology and Human Values
JF - Science Technology and Human Values
IS - 3
ER -