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708 DEMIRALP ET AL.

those owned by women in terms of firm survival, analysis compares characteristics and outcomes of
sales, profit, and employment across sectors (4,5). women and men entrepreneurs in STEM fields;
There also exists evidence of a gender gap in the women entrepreneurs in STEM and non-STEM fields;
successful commercialization of research and devel- and self-employed women and women in wage/salary
opment investments, and this gap widens for firms employment in STEM fields. The empirical analysis
operating in STEM fields (6). employs two proxies for entrepreneurship based on
The literature offers two potentially complemen- availability in the data: self-employment in examin-
tary frameworks to explain the frequency with which ing ACS data and business ownership in examining
women pursue STEM training and engage in com- SBO data. Furthermore, it focuses on commercial-
mercialization in STEM firms. The first suggests that ization of scientific innovations in its initial phase:
internal motivations, driven by personal preferences, the creation of intellectual property.
prompt women to pursue training and professional Second, the report examines prior research and
work in fields other than STEM. Some studies suggest policy literature related to women’s entrepreneur-
that women may pursue STEM commercialization ship and commercialization outcomes in STEM
activities less frequently than men because these fields fields. Together, the literature review and data anal-
are not perceived as contributing to research with ysis identify and explore important themes related
socially meaningful outcomes, a work characteris- to women in STEM, including the prevalence of
tic that women tend to prioritize in career choices STEM entrepreneurship among women, the role of
(7). The second framework suggests that external STEM education in STEM entrepreneurship, and the
exogenous barriers discourage women’s participation characteristics of owners and firms that are actively
in STEM training and entrepreneurship and limit engaged in STEM entrepreneurship and their com-
women’s commercialization outcomes (8). External mercialization outcomes. Finally, the report discusses
barriers include limitations to accessing financial policy recommendations related to women’s educa-
capital for education or entrepreneurship, gender dis- tion, entrepreneurship, and commercialization in
crimination, limited access to important networks, or STEM—identified through the literature review and
hierarchical and rigid institutional structures, which policy scan—to illustrate policy implications of the
lack network-oriented features demonstrated to ben- analysis findings.
efit women (8,9). These obstacles may affect women’s
educational and career decisions at various stages of IDENTIFYING STEM ENTREPRENEURS IN
their development. In this vein, women’s scientific EMPIRICAL ANALYSIS
career progression in STEM fields has been likened
to a “leaking pipeline,” in which the barriers that Identifying STEM Fields
women face hinder them from moving forward to A key methodological decision in the empirical
progressive stages in their careers, such as leading analysis undertaken in this study is the identifica-
the commercialization of discoveries. These frequent tion of STEM workers and entrepreneurs. As an
“leaks” may limit the number of women working in acronym, STEM covers the fields of science, tech-
STEM at senior levels and may additionally hold nology, engineering, and mathematics. The National
implications for women’s commercialization out- Science Foundation uses a broader definition of
comes over their career cycles (10). STEM that also includes social sciences and STEM
This report presents an examination of innovation education and learning research. Although these
among women in STEM fields by identifying gaps definitions clearly link to academic disciplines, how
in their entrepreneurial outcomes and highlighting they map to workers and jobs is less well-defined.
future opportunities for policy improvements. First, For the purpose of this study, STEM workers and
it presents results of a descriptive data analysis using entrepreneurs were identified based on the STEM
data from the 2015 American Community Survey occupational classification developed by the Standard
(ACS) and the U.S. Census Bureau’s 2007 and 2012 Occupational Classification Policy Committee
Survey of Business Owners (SBO). This empirical (SOCPC). SOCPC’s guidelines identify life and