Hidden patterns. Using social network analysis to track career trajectories of women STEM faculty

• DOI: https://doi.org/10.1108/EDI-09-2017-0183
• Date: 11 March 2019
• Published date: 11 March 2019
• Pages: 265-282
• Author: Regina Collins,Nancy Steffen-Fluhr
• Subject Matter: Hr & organizational behaviour

Hidden patterns

Using social network analysis to track career

trajectories of women STEM faculty

Regina Collins

Office of Institutional Effectiveness, New Jersey Institute of Technology, Newark,

New Jersey, USA, and

Nancy Steffen-Fluhr

Department of Humanities, College of Science and Liberal Arts,

New Jersey Institute of Technology, Newark, New Jersey, USA

Abstract

Purpose –The purpose of this paper is to describe how one group of ADVANCE Project researchers

investigated faculty co-authorship networks to identify relationships between women’s positions in these

networks, their research productivity and their advancement at the university –and to make those

relationships transparent.

Design/methodology/approach –Multiple methods for capturing faculty network data were evaluated,

including collecting self-reported data and mining bibliometric data from various web-based sources. Faculty

co-authorship networks were subsequently analyzed using several methodologies including social network

analysis (SNA), network visualizations and the Kaplan–Meier product limit estimator.

Findings –Results suggest that co-authorship provides an important way for faculty to signal the value of

their work, meaning that co-authoring with many others may be beneficial to productivity and promotion.

However, patterns of homophily indicate that male faculty tend to collaborate more with other men, reducing

signaling opportunities for women. Visualizing these networks can assist faculty in finding and connecting

with new collaborators and can provide administrators with unique views of the interactions within their

organizations. Finally, Kaplan–Meier survival studies showed longitudinal differences in the retention and

advancement of faculty based on gender.

Originality/value –Together, these findings begin to shed light on subtle differences that, over time, may

account for the significant gender disparities at STEM institutions, patterns which should be investigated

and addressed by administrators. Lessons learned, as well as the novel use of SNA and Kaplan–Meier in

investigating gender differences in STEM faculty, provide important findings for other researchers seeking to

conduct similar studies at their own institutions.

Keywords Gender, Academic staff, Sex and gender issues, Women workers, Higher education

Paper type Research paper

Introduction

During the second phase of a National Science Foundation (NSF) Institutional

Transformation grant (2006–2013), the ADVANCE Project at the New Jersey Institute of

Technology (NJIT) implemented a novel strategy: applying social network analysis (SNA) to

faculty co-authorship data in order to better understand and address the factors that affect

the careers of women faculty in science, technology, engineering and math (STEM). This

paper describes the methodological challenges involved in studying the networks of STEM

faculty –and the opportunities that SNA affords to both individuals and institutions by

making hidden relational patterns more visible.

The university’s2005 Status of Women Faculty Report indicated thatat NJIT, as at other

similar institutions, women faculty felt isolated and outside the information loop

(e.g. August and Waltman, 2004). The NJIT–ADVANCE Institutional Transformation grant

was designed to address these concerns. In its initial phase (2006–2010), the project targeted Equality, Diversity and Inclusion:

An International Journal

Vol. 38 No. 2, 2019

pp. 265-282

© Emerald PublishingLimited

2040-7149

DOI 10.1108/EDI-09-2017-0183

Received 14 September 2017

Revised 17 January 2018

Accepted 13 April 2018

The current issue and full text archive of this journal is available on Emerald Insight at:

www.emeraldinsight.com/2040-7149.htm

The authors gratefully acknowledge the work of many individuals who assisted in this research,

particularly Dr Yi-Fang (Brook) Wu, Dr Mingzhu Zhu, Dr Katia Passerini and Dr Christopher Markson.

265

Career

trajectories of

women STEM

faculty

isolationby stimulating research collaborationsamong faculty through activities such as seed

money and travel grants for woman-led research project teams; interdisciplinary knowledge

exchanges; cross-sector research showcases; and an informal Research Café. Simultaneously,

the project studied the existing patterns of collaboration through networks of faculty

co-authorship. The goal was to determine whether increased research collaboration was

advantageous for women. In this earlier study, statistically significant correlations between

collaboration (calculated using network centrality measures) and career advancement

suggested that it was. In its second phase (2010–2013), NJIT–ADVANCE built on that work,

moving from concept to deeper analysis and sustainable application. The project’sprimary

research goal was to demonstrate that SNA and mapping (network visualization) could be

used at NJIT and elsewhere to support more efficient faculty career management, including

mentoring –and to visualize subtle institutional changes occurring over time.

From the beginning, NJIT–ADVANCE was distinctive in its focus on the intersection of

research collaboration and academic advancement (promotion in rank). In order to design

career interventions effectively and assess their actual impact, NJIT–ADVANCE researchers

needed to collect baseline network, productivity and promotion and tenure (P&T)data on all

STEM faculty and find sustainable (scalable) means of analyzing changes in that data over

time. In recent years, a growing number of studies haveinvestigated the correlation between

network structure (as measured by various social network centrality measures) and

productivity(as measured by publicationor citations counts), e.g. Abbasiand Altmann (2011).

However, there have been remarkably few US studies that look at network structure and

promotion, despite the fact that promotion is the clear measureof career success in academia.

This study was therefore informed by a central research question:

RQ1. What is the relationship among collaboration (network structure), productivity and

advancement in rank?

Background

Numerous studies have found that women and under-represented minority (URM) faculty in

STEM feel that they are more isolated than their peers (e.g. August and Waltman, 2004;

Belle et al., 2014; Xie and Shauman, 2003) and have less influence in their departments (Carr

et al., 2003; Niemeier and Gonzalez, 2004). Such feelings, in turn, are linked to lower job

satisfaction, reduced career success and higher turnover rate (Hart, 2016; Shore et al., 2011).

Early approaches to addressing these issues focused on an “add-women-and-stir approach”

(Etzkowitz et al., 2000). However, when NSF replaced POWRE with the ADVANCE Program, it

shifted the foundation’s focus from individual empowerment to institutional transformation. The

NJIT–ADVANCE project mirrored this shift in focus, proposing a novel method of investigating

gender differences within STEM institutions using the power of social networks as

“transformational engines”(Ibarra et al., 2005) while addressing their paradoxical invisibility

(O’Reilly, 1991). The NJIT–ADVANCE strategy had two goals: to develop techniques, tools and

practices that could provide potential faculty outsiders –especially women –with inside

knowledge of network pathways, and simultaneously give university administrators a more

subtle means of identifying potentially problematic characteristics of the units they manage

(Basole, 2016). In this effort, NJIT–ADVANCE was guided by the core belief that data

transparency is not only the key to measuring change, but also it is the key to motivating change.

The project sought to actualize Christakis and Fowler’s (2009) observation that, “To

know who we are, we must understand how we are connected”by making hidden

organizational network structures visible to the faculty embedded in them (Niehaus and

O’Meara, 2015; O’Reilly, 1991; Tichy et al., 1979). To accomplish this goal, NJIT–ADVANCE

researchers selected SNA, a methodology rooted in “sociometry”(Moreno, 1934; Scott, 1988),

to explore networks of faculty collaboration through co-authorship. In SNA, ego networks

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