The Researcher Journey
Through a Gender Lens

An examination of research participation, career
progression and perceptions across the globe

Contents
Foreword

4

Chapter 2

Executive Summary

6

Research Footprint

32

Key Findings

33

Introduction

34

Author Publication Output

36

Field-Weighted Citation Impact

40

Grants Awarded

42

Number of Patent Applications

43

Case Study: Assessing genderbalance among China’s authors

45

Expert Interview
Charlina Vitcheva, MA, MS, Acting DirectorGeneral, Joint Research Centre, European
Commission

49

Conclusion

52

Chapter 1

Research Participation

8

Key Findings

9

Introduction

10

Authors of Research Publications

12

Case Study: Gender diversity withinsubfields of medicine

22

Grant Awardees

27

Inventors and Patent Assignees

29

Conclusion

31

Chapter 3

PAGE 2 The Researcher Journey Through a Gender Lens

Publishing Careers and Mobility

54

Key Findings

55

Introduction

56

Assessing the Continuity of Authors
Over Time

57

Gender and Researcher Mobility Trends

61

Expert Interview
Miyoko O. Watanabe, PhD, Director, Officefor Diversity and Inclusion, Japan Scienceand Technology Agency

65

Conclusion

67

Chapter 4

Collaboration Networks

68

Key Findings

69

Introduction

70

Network Centrality of Focal Authors

72

Characteristics of Collaboration Ties

74

81
Expert Interview
Sarah Sharples, CErgHF, FIET, FIEHF, PhD,
MSc,BSc (hons), PGCAP, Pro-Vice-Chancellor
for Equality, Diversity and Inclusion,
University of Nottingham
Conclusion

Appendices118

Appendix A
Methods and Experimental Approach

119

Appendix B
Supplemental Data

134

Appendix C
Elsevier’s 2019 Researcher Survey Results

166

Appendix D
Authors and Contributors

179

84

Chapter 5

Researcher Perspectives

86

Key Findings

87

Introduction

88

Analyzing the Diversity of Opinions
on the Role of Gender in Academia

89

Interventions Towards Achieving
Gender Diversity and Equity:
Comments and Suggestions

108

Expert Interview
Sandra W. Robert, CAE, Chief Executive
Officer, Association for Women in Science

115

Conclusion

117

Contents PAGE 3

The Researcher Journey
Through a Gender Lens

Foreword
At Elsevier, our mission is to advance science andto improve healthcare outcomes through quality
information and analytics. The only way we, andothers, can make a lasting impact on the societal
challenges of our times is by harnessing the fullcontribution of all stakeholders in the global
research and healthcare community. Promoting
gender diversity and inclusion in research throughan evidence-based, measurable approach is an
important part of this ongoing effort. We havebeen applying this approach to achieve a betterbalance of gender participation in research and areincreasingly focusing on how gender is factored
into research.
In this light, I am pleased to share our latest report:
The Researcher Journey Through a Gender Lens.
The past fifty years have seen enormous strides forand by women in research. Women now comprisea greater share of science, technology, engineering,mathematics (STEM) and medicine graduates thanever before, and there is increased focus and energy
on balanced participation, factoring gender into
research and research on gender itself.
Yet, our latest findings indicate that disparities still
linger, with slower growth of articles publishedby women, higher numbers of women leaving
research and understudied research areas.
This report also highlights that women are notparticipating in collaboration networks at the samelevel as men, potentially impacting their career
progression. On average, men have more coauthors than women, with a tendency to collaborate
with those of the same gender across the subject
areas and regions studied, demonstrating that wehave more work to do to address issues that cut
across diversity and inclusion.

PAGE 4 The Researcher Journey Through a Gender Lens

As the first woman CEO in Elsevier’s 140-year
history, I am proud and privileged to play a rolein examining the consequences of women’s
underrepresentation in research and to implement
solutions to drive more inclusive research. We
have the responsibility to combine quality content
with the latest in data analytics to gain robust
insights into areas of gender imbalance anddevelop targeted strategies, such as recalibrating
conferences, editorial boards and the peer review
process, so research is curated to be more inclusive.
This new study builds on our previous tworeports—Gender in the Global Research Landscapeand Mapping Gender in the German Research Arena—by examining critical aspects of contribution,
performance and influence through a gender lens.
The report includes quantitative analyses of newareas and themes not covered in our earlier reports
and, for the first time, incorporates a qualitative
survey. We feel accountable to continue to sharepowerful, data-driven insight with researchers,
governments, funders and institutions worldwide
to inspire targeted initiatives and to inform policy.
These reports are part of Elsevier’s broader
commitment to gender diversity and inclusion,
as a member of the global research community
and in support of the United Nations’ Sustainable
Development Goal 5 to achieve gender equality
and empower all women and girls. Throughour Gender Working Group, we are continuallyrefining key processes, principles and systems
so that we can support the most robust researchin the most equitable and inclusive way. We are
actively targeting greater gender diversity for ourjournal editorial boards, reviewers and invitedconference speakers, and are seeking to address
the various layers where implicit bias can come into

play throughout the peer review process. Across
our portfolio of journals, we have significantly
enhanced editorial policies and guidance to authors
on reporting about sex and gender in researchstudies and the use of inclusive language.
We are deliberately working to foster an inclusive
culture across Elsevier, including enhanced
development paths for women into seniorleadership roles and more flexible benefits to foster
greater work-life balance. This effort is spearheaded
by our Global Head of Inclusion & Diversity andsupported by the energy and passion of our 7,500
employees around the globe.
I am also excited to share that we are launchingan Inclusion and Diversity Advisory Board, whichbrings together the passion and thoughtful
contributions of preeminent leaders fromacross the international research and healthcarecommunity. It is a great privilege to work withsuch a distinguished group of independent leaders
towards finding lasting solutions to unlock the fullpotential of academic and applied research throughgreater diversity.
I hope the findings of our latest report will provide
useful insights and drive action, by also learningfrom disciplines and countries where there has been
more success in making progress. I look forward tocollaborating with all stakeholders who share ourobjective of enhancing gender equity in research.

Kumsal Bayazit
Chief Executive Officer, Elsevier

We feel accountable to continue toshare powerful, data-driven insight withresearchers, governments, funders andinstitutions worldwide to inspire targeted
initiatives and to inform policy.

Foreword PAGE 5

The Researcher Journey
Through a Gender Lens

Executive Summary
Gender diversity and inclusion are of growing
importance and focus in many sectors, including
business, education, government and research.
Increasing gender diversity has a positive impact
on productivity, boosts problem-solving andincreases innovation – all essential outcomes fortackling the great challenges of our time, fromhealth to food security, from climate change tosustainable communities.

parity, particularly among authors with a shortpublication history and in many subject areas
within the life and health sciences. In somesubjects, notably nursing and psychology, women
now represent the majority of authors. Conversely,
men are better represented among authors witha long publication history, across all subject
areas within the physical sciences and as last andcorresponding authors.

As part of Elsevier’s ongoing efforts to promote
gender diversity and advance gender equity inresearch using an evidence-based approach, wedeveloped this latest report to understand how
gender impacts the researcher journey. Drawing
on robust data sets, we analyzed information aboutauthors of academic publications, grant recipientsand patent applicants to gain insights into trends
in gender-based representation across 15 countries
and the EU28.

In addition to the general global trends, there were
notable country-specific findings. For example,
Argentina was the closest to gender parity amongauthors overall, while Japan had the lowest ratioof women to men among authors in all subject
areas. Spain and Mexico had the largest increases
in the proportion of women among inventors. In
many countries, however, the proportion of womenamong grant recipients corresponds with women’s
underrepresentation as last and corresponding
authors on papers. Moreover, among patentapplicants, women were very poorly represented
and little change was observed over time,suggesting high gain potential in this segment of
the innovation pipeline.

In recent decades there has been significant
progress in terms of women’s participation in
research and we are seeing an increased focus onfactoring gender into research.
However, our latest report shows that disparities
still exist, demonstrating that we have more work to
do to address issues that cut across diversity as wellas inclusion.

In research authorship, we are closer togender parity now than a decade ago,
with women continuing to publish fornearly as long as men over the courseof their careers.
In all the countries and regions featured in thisreport, the increase in women authors is closing
a gender gap in terms of participation. In someresearch areas, authorship is approaching gender

PAGE 6 The Researcher Journey Through a Gender Lens

However, the ratio of women tomen as authors decreases over time,
contributing to men publishing
more, having greater impact as well
as exposure to international careeradvancement.
The ratio of women to men declined from the timeof first publication to 10 years later in all countries
and regions, except for Portugal. Moreover, in every
country, the percentage of women who continue topublish over time is slightly lower than for men.
International experiences are associated with ahigher retention of authors, and men are more
likely than women to travel outside their home

country during their research careers. Among those
who publish outside their home country, men are
more likely to continue to publish than women,
further reflecting a retention disparity. Amongauthors who traveled internationally, in mostcountries and in the EU28, men publish more andhave a slightly higher citation impact than women.

However, women and men are equally connected
to second-order collaborators and to international
co-authors – except in the EU28, where men
establish international collaborations slightly morethan women do. Notably, both men and women
preferentially collaborate with authors of thesame gender.

Women have a smaller footprint in
the research landscape and fall behind
men among grant awardees and patentapplicants.

Attitudes toward gender issues vary,necessitating tailored communication
and action.

While having a diverse workforce of researchers
is important, it is equally important for individualcareer progression that the researcher footprint—
including publications and citations, grant awards
and patent applications—reflects growth inparticipation.
However, men have a larger research footprintin general: they publish more than women, areawarded more grants than women, and apply
for more patents than women. This is a trend
apparent in every country examined. Furthermore,on average, the citation impact of men’s firstauthor publications is higher than that of women’s,
intimating a gender bias in citation practice.

Collaboration approaches differ bygender as men have more direct
collaborators than women, although
women and men are equally central totheir networks overall.

Researcher attitudes towards the role of genderin academia vary, guided by the importance theyplace on gender diversity and inclusion and by
how fair they perceive the academic system tobe. This was the case for several topics, from theimpact of gender on recruitment and promotion
to interventions aimed at increasing gender
diversity. There was general agreement thatfamily duties can negatively impact women’s
research careers. Differing opinions on thecauses of gender bias were reflected in different
interventions suggested by respondents. Thesefindings speak to the need for institutions,organizations and policymakers to customize thecommunication strategies related to their gender
diversity and inclusion initiatives to account fordifferent perspectives, so that those initiatives canfully succeed.

Broadly, across subject areas and countries, men
tend to have more co-authors than women do,with the gap widening as publication history
increases, which likely contributes to men
having a higher publication output than women.

Executive Summary PAGE 7

Chapter 1

Research 			Participation
Assessing gender diversity among researchers

Key Findings• In all countries studied and the EU28, the ratio of
women to men among all authors is closer to parity
during a recent 5-year period compared with adecade ago.
• Men are more highly represented among authors
with a long publication history while women arehighly represented among authors with a shortpublication history.
• In most countries, the ratio of women to men
among authors is lowest in the physical sciences
and highest in the life and health sciences.
Nursing and psychology stand apart with more
women than men among authors. Japan has thelowest ratio of women to men among authors inevery subject area.
• The greatest increase in the proportion of womenamong authors is seen in nursing and psychology
and the smallest increase is seen in the physicalsciences.
• Last authors and corresponding authors consist of
proportionally more men than women comparedwith the overall author population in every country.
• In many countries, the proportion of women among
grantees closely reflects the proportion of womenamong corresponding and last authors.
• The ratio of women to men among inventors
and assignees is very low compared to the ratio
observed for authors and grantees. Most countries
show very modest changes in these ratios overtime. Spain and Mexico stand apart for having
the largest increases in the proportion of womenamong inventors.

Research Participation PAGE 9Research Participation

Introduction
Studies have shown that gender diversity in theworkforce correlates with profitability and value
creation1, and that gender-diverse leadership
improves productivity2. In an age when researchmust demonstrate return on investment, thebenefits of gender diversity are increasingly
important. Furthermore, research is increasingly
collaborative, and studies have demonstrated thatthe proportion of women in a group is one ofthree key factors that correlate with the collective
intelligence of that group.3 Yet, the gender gap
among researchers within the global scientificworkforce persists across subject areas andgeographic regions.4 In 2018, 28.8% of researchers
globally were women per the UNESCO Institutefor Statistics.5 Elsevier’s 2017 report, Gender in1

the Global Research Landscape, reported that the
proportion of women among researchers ranges
from 20% to 49% across 12 countries and regions.6
Participation in research by women also varies bysubject area, with relatively higher proportionsof women in the biomedical sciences and lower
proportions in the physical sciences. Suboptimal
gender balance among researchers increases therisk of suboptimal productivity, creativity andinnovation within the global scientific endeavor.

McKinsey & Company. (2018). Delivering through Diversity. Retrieved from: www.mckinsey.com/~/media/mckinsey/business%20functions/organization/our%20insights/delivering%20through%20diversity/
delivering-through-diversity_full-report.ashx. Accessed November 24, 2019.; Zhang, L. (forthcoming). An institutional approach to gender diversity and firm performance. Organization Science. Retrieved from:www.hbs.edu/faculty/Publication%20Files/Final_version_6cb1dbd5-9c48-4a1c-9afa-237da2a1a7b4.pdf. Accessed November 24, 2019.

2 Dezso, C. L., & Ross, D. G. (2011). Does female representation in top management improve firm performance? A panel data investigation (March 9, 2011). Robert H. Smith School Research Paper No. RHS 06-104.
Retrieved from: papers.ssrn.com/sol3/papers.cfm?abstract_id=1088182. Accessed November 24, 2019.
3 Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evidence for a collective intelligence factor in the performance of human groups. Science, 330(6004), 686-688. doi: 10.1126/
science.1193147
4 Charlesworth, T., & Banaji, M. (2019). Gender in science, technology, engineering, and mathematics. Journal of Neuroscience, 39(37), 7228-7243. doi: 10.1523/JNEUROSCI.0475-18.2019; Fox, M.,
Whittington, K., & Linkova, M. (2017). Gender, (in)equity, and the scientific workforce. In: Handbook of Science and Technology Studies. Cambridge, MA: MIT Press.; Elsevier. (2015). Mapping Genderin the German Research Arena. Retrieved from: www.elsevier.com/research-intelligence/resource-library/gender-2015. Accessed October 28, 2019.; United Nations Educational, Scientific and Cultural
Organization. (2015). UNESCO Science Report: Towards 2030. Retrieved from: unesdoc.unesco.org/in/documentViewer.xhtml?v=2.1.196&id=p::usmarcdef_0000235406&file=/in/rest/annotationSVC/
DownloadWatermarkedAttachment/attach_import_871d5667-bd86-4feb-a045-f802628d2f48%3F_%3D235406eng.pdf&locale=en&multi=true&ark=/ark:/48223/pf0000235406/PDF/235406eng.
pdf#%5B%7B%22num%22%3A647%2C%22gen%22%3A0%7D%2C%7B%22name%22%3A%22XYZ%22%7D%2Cnull%2Cnull%2C0%5D. Accessed November 24, 2019.
5

UNESCO. (2018). Women in Science. Fact Sheet No. 51. June 2018 FS/2018/SCI/51. Retrieved from: uis.unesco.org/sites/default/files/documents/fs51-women-in-science-2018-en.pdf. Accessed October 23, 2019.

6 Elsevier. (2017). Gender in the Global Research Landscape. Retrieved from: www.elsevier.com/research-intelligence/campaigns/gender-17. Accessed October 23, 2019.

PAGE 10 The Researcher Journey Through a Gender Lens

The reasons underlying the gender gap in thescientific workforce—and how to address it—
is a topic of intense study. The She Figures 2018
report noted near gender parity among researchersat the graduate level, but far fewer women at
top positions within their fields.7 This underrepresentation of women in leadership positions
has been attributed to various factors, fromgender differences in STEM (science, technology,
engineering and mathematics) education, tochallenges with work-life balance and systemic
gender bias in hiring, promotion, publishing andfunding.8
Diversity within the scientific workforce, including
gender diversity, brings unique perspectives,
drives creativity and innovation and provides newcontexts for understanding and applying researchfindings.9 Acknowledgment of the gender gap inresearch and its negative impact on progress has
led to various institutional, national and global
efforts to address the factors that steer girls andwomen away from seeking or staying in a research
career.10 Although a gender gap persists in many
fields and countries, and the gap is closing more
slowly in certain subject areas and countries,11Elsevier noted in their 2017 report that the
proportion of women among researchers increased
from 1996–2000 to 2011–2015 in all subject areas
and geographies studied.12

Understanding the dynamics of participation ofmen and women in research will help inform
strategies to further reduce the gender gap in the
global scientific workforce.13 This chapter describes
the scientific workforce and how it has changed
over time across 15 countries and the EU28 in
26 subject areas, comparing the number of men
and women among researchers who are authorsof scientific publications, awardees of grants andinventors and patent holders. Using comprehensive
data sources such as Elsevier’s Scopus and Funding
Institutional databases and the European Patent
Office (EPO) Worldwide Patent Statistical Database,
PATSTAT, this analysis provides a multifaceted viewof the research community along three of the main
activities that researchers undertake: publishingresearch (scholarly communication), obtaining
grant support (research funding) and registering
patents (research innovation).
Such evidence-based findings are a crucial
step towards greater gender diversity: byunderstanding where we stand, based on where
we have come from and how we have achieved
progress, we can determine how to continue on ourjourney towards even greater gender balance in theworld of research.

7 European Commission Directorate-General for Research and Innovation. She Figures 2018. (2019). Brussels, Belgium: European Union. doi: 10.2777/936; National Research Council. (2010). Gender differencesat critical transitions in the careers of science, engineering, and mathematics faculty. Retrieved from: doi.org/10.17226/12062. Accessed October 23, 2019.; Gibney, E. (2016). Women under-represented in world’s
science academies. Nature. February 26. Retrieved from: www.nature.com/news/women-under-represented-in-world-s-science-academies-1.19465. Accessed October 23, 2019.
8 Charlesworth, T., & Banaji, M. (2019). Gender in science, technology, engineering, and mathematics. Journal of Neuroscience, 39(37), 7228-7243. doi: 10.1523/JNEUROSCI.0475-18.2019; Association of Women in
Science. (2019). Transforming STEM Leadership Culture. Retrieved from: www.awis.org/leadership-report/. Accessed October 28, 2019.
9 Nielsen, M., Bloch, C., & Schiebinger, L. (2018). Making gender diversity work for scientific discovery and innovation. Nature Human Behavior, 2(10), 726-724. doi: 10.1038/s41562-018-0433-1
10 Beeler, W., Smith-Doody, K., Ha, R., Aiyar, R., Schwarzbach, E., & Solomon, S. (2019). Forum institutional report cards for gender equality: lessons learned from benchmarking efforts for women in STEM. Cell
Stem Cell, 25(3), 306-310. doi: 10.1016/j.stem.2019.08.010
11 Holman, L., Stuart-Fox, D., & Hauser, C.E. (2018). The gender gap in science: how long until women are equally represented? PLoS Biology, 16(4), e2004956. doi: 10.1371/journal.pbio.2004956
12 Elsevier. (2017). Gender in the Global Research Landscape. Retrieved from: www.elsevier.com/research-intelligence/campaigns/gender-17. Accessed October 23, 2019.
13 Coe, I., Wiley, R., & Bekker, L. (2019). Organizational best practices toward gender equality in science and medicine. Lancet, 393(10171), 587-593. doi: 10.1016/S0140-6736(18)33188-X

Research Participation PAGE 11

Research Participation

Authors of
Research Publications
Authorship of research publications is one waythat researchers contribute to the advancementof knowledge. The demographics of the author
pool may reflect gender differences if researchdoes not appeal to women and men to the same
degree. The appeal of research to women compared
to men can differ because of cultural differencesin how research is portrayed or perceived, or how
welcoming the research environment is to womencompared to men. This difference in the appealof research ultimately manifests as differencesin who is recruited and retained as part of theresearch workforce. In 2019, Elsevier’s Customer
Insights team conducted a survey to examine theperceptions of active researchers (self-identified
as spending at least 20% of their academic/work
activity conducting research on an ongoing basis)around career progression and gender balance inscholarly research. The survey revealed that 37% ofactive researchers think that gender imbalance intheir field may be due to a lack of encouragementof women to pursue education or careers in thatfield starting from an early age. In addition, 42% of
women surveyed described their workplace culture
as gender-biased, and 38% of women reported
bias or discrimination in recruitment, hiring andpromotion processes (Appendix C, Figure C.1).
To provide greater insight into who participates in
research as an author, we analyzed the active author
populations for 15 countries and the EU28 during
the periods 1999–2003 and 2014–2018.
We found a trend towards gender parity amongauthors when comparing active authors in
2014–2018 to those in 1999–2003 in all countries
studied and the EU28 (Figure 1.1 and supplemental
data Table B.1). This finding is consistent with theglobal research community’s perceptions, with
61% of active researchers surveyed by Elsevier

PAGE 12 The Researcher Journey Through a Gender Lens

indicating that there are more women in research
now compared to 10 years ago (Appendix C,
Figure C.2). For most countries, the ratio washigher in 2014–2018 compared to 1999–2003
by approximately 20 women for every 100 men.
Portugal showed the greatest increase in the ratioof women to men authors, from 63 women per 100
men in 1999–2003 to 94 women per 100 men in
2014–2018. Japan showed the smallest change overtime, from 11 women per 100 men in 1999–2003 to
18 women per 100 men in 2014–2018. Among thecountries analyzed, Argentina stood out for being
the closest to parity among its authors in the period
2014–2018, with 104 women per 100 men.
As previously noted, cultural differences can explain
the appeal of research to women compared to men
and it is therefore striking that while Argentina
shows a larger number of women in researchthan men, the Global Gender Gap Report 2020
from the World Economic Forum (http://www3.
weforum.org/docs/WEF_GGGR_2020.pdf ) shows
Argentina in 30th position with a Gender Gap Indexof 0.746. As a point of comparison, the index forGermany, which is ranked 10th, is 0.877 but shows
lower proportion of women in research in our
analysis. Similarly, while our findings show a higher
proportion of women in research in Portugal, thecountry’s Gender Gap Index is 0.744 (ranked 35th).
Further investigation might reveal an explanation
for this difference between the research world
and wider society. On the other hand, Japan’s
low Gender Gap Index of 0.652 (ranked 121st) is
consistent with the low proportion of women in
research identified in our analysis.

More men

FIGURE 1.1

Gender ratio among
active authors during
the periods 1999–2003
and 2014–2018 in eachcountry and the EU28.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

More women

100

111

125 143 167 200 250 333 500 1000 ∞

90

80

100

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

60

50

40

30

20

10

0

Argentina
BrazilMexicoCanada
USA
EU28
UK

KEY
1999–2003
2014–2018

Portugal
Spain
France
Italy
Netherlands

FIGURE 1.1 TAKEAWAY:

Germany

In all countries and theEU28, the ratio of women
to men is closer to parity
in the period 2014–2018
compared to 1999–2003.

Denmark
Australia
Japan
Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

Parity between men and women

70

50

40

30

20

10

0

More women

HOW WE CONDUCTED THE AUTHOR-LEVEL ANALYSESFor each period analyzed, we defined active authors as those who authored at least two
publications during the study period. To ensure that we did not exclude junior authors, we
included any author who had their first publication during the period 1999–2003 if they had
at least one more publication in the five years after the first publication, and any author who
had only one publication during the period 2014–2018 if their first publication was publishedduring that period. Authors were counted towards a country’s author count if more than 30%of their publications during the period indicated an affiliation with that country (through theinstitutional affiliations associated with that author on the publication). Countries included inthese analyses had at least 30,000 active authors from 2014 to 2018 for whom a gender could
be inferred. Detailed methods are available in Appendix A.

Research Participation PAGE 13

The findings in Figure 1.1 reflect the total author
population in each country regardless of field ofstudy or time since first publication. However, we
expected to find considerable differences acrossthese parameters even within the same country.
To clarify whether author ratios vary amongauthors with different publication start dates, wedisaggregated the authors based on when they firstpublished. This approach allowed us to assess how
generational effects contribute to author parity byusing publication start date as a proxy for age, withthe assumption that, for example, if an author isactively publishing during the period 2014–2018
and their first publication was in 1999, they arelikely older than someone whose first publication
was in 2010.
We assigned the active authors from the period
2014–2018 into four defined categories, fromthose with the longest publication history (groupA) to those with the shortest publication history(group D) according to the following parameters:group A – first publication in 2003 or prior;group B – first publication in 2004–2008; groupC – first publication in 2009–2013; group D – firstpublication in 2014–2018.

PAGE 14 The Researcher Journey Through a Gender Lens

In every country analyzed, the ratio of women tomen authors was closest to parity among thosewith the shortest publication history (group
D; likely the youngest group of authors), andfurthest from parity among those with the longest
publication history (group A; likely the oldest groupof authors), with groups C and B in between (Figure1.2). Those with the shortest publication history
also represented the largest group of authors ineach country and the EU28 (supplemental data
Figure B.1), indicating that author ratios at themost junior levels are an important underlying
factor driving the overall author ratios seen at thecountry level. In some countries, particularly thosecountries at or close to gender parity overall, suchas Argentina and Portugal, the most junior groups
consisted of more women than men authors. For
most countries, there were 30-40 more women per
100 men in the most junior group compared to themost senior group of authors. The least differencein gender balance among the four author groups
was seen in Argentina, which was also closest togender parity overall, and in Japan, which had thelowest ratio of women to men authors regardlessof author publication history. These results suggest
generational differences in the numbers of womenand men authors. In Chapter 3, we assess whether
there are differences in how many authors continue
to publish over time and whether the rate ofcontinued authorship differs for women compared
to men.

1.2
More men

FIGURE 1.2

Gender ratio among
active authors during theperiod 2014–2018 in eachcountry, grouped basedon year of author’s firstpublication.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Group A

Argentina

Group B
Group CGroup DA

BrazilB
CD
A

MexicoB
CDACanadaKEY

GROUP

YEAR OF FIRSTPUBLICATION

A

2003 or priorB

2004–2008C

2009–2013D

2014–2018

B
C
D
A

USA

B
C
D
A

EU28

B
C
D
A
B

UK

C
D
A

FIGURE 1.2 TAKEAWAY:

Men are more highly
represented amongauthors with a long
publication history
while women are highly
represented amongauthors with a shortpublication history.

Portugal

B
C
D
A

Spain

B
C
D
A

France

B
C
D
A

Italy

B
C
D
A

Netherlands

B
C
D
A

Germany

B
C
DA

Denmark

B
C
D
A

Australia

B
C
D
A

Japan

B
C
D

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenResearch Participation PAGE 15

Country-level gender statistics are greatly
influenced by author and gender distribution
across subject areas. Across the countries andregion studied, authors in medicine are themost highly represented group, representing
15% (in Germany) to 23% (in Italy) of all authors(supplemental data Figure B.2). Authors inbiochemistry, agricultural sciences and engineering
represent 10-13% of authors in some countries.
Authors in all other subject areas represent lessthan 10% of authors in the country.
Figure 1.3 shows that among active authors during
the period 2014–2018, the lowest ratio of women
to men was observed in the physical sciences(median ratio among countries ranged from 20
women per 100 men in mathematics to 51 womenper 100 men in environmental science). In manylife sciences and health sciences subject areas,
the median ratio among the countries analyzed
was close to parity. Nursing was an exception
among the health sciences subject areas, in thatwomen predominated. Among the social sciences,
psychology was the exception in that women
predominated in most countries. In all othersocial sciences subject areas, the median ratioof women to men was below parity but was still
above the median observed for subject areas in thephysical sciences. These data are consistent withthe research subject area demographics reported
in Elsevier’s 2019 survey of active researchers in the
global research community (Appendix C, FigureC.3). We also found that broad observations madeat the country level were reflected within eachsubject area, with the highest ratio of women tomen observed for Argentina and the lowest ratio
observed for Japan across all subject areas.

In every subject area, among the countries
analyzed, the median ratio of women to men
among active authors in 2014–2018 was higher
than the median ratio among authors in 1999–2003(supplemental data, Figure B.3). The smallest
increase in median ratio was seen for subject areasin the physical sciences, where the median in 2014–2018 was 6 to 8 more women per 100 men thanin 1999–2003 in several subject areas (computerscience, mathematics, physics & astronomy,materials science, engineering, energy). Among thephysical sciences, environmental science showed
the greatest increase in the proportion of women,with 18 more women per 100 men in 2014–2018
than in the previous period (based on median ratio
among countries analyzed). In contrast, the lifeand health sciences showed the greatest increase
in women as a proportion of men, with medians
ranging from 20 more women per 100 men inbiochemistry to 64 more women per 100 men innursing in 2014–2018 compared with 1999–2003.
The changes observed in nursing were interesting
given that, in most countries, even though women
predominated as authors in 1999–2003, theproportion of women among authors in nursing
was even higher in 2014–2018 for each country. For
example, among the countries analyzed, Australia
had the highest proportion of women among active
authors in nursing in 1999–2003, with 171 womenper 100 men. This increased to 245 women per 100
men in 2014–2018.

HOW WE DID THE SUBJECT-LEVEL ANALYSES

To examine how author gender distribution varies within research disciplines, we assessed genderratios using the Scopus journal classification system, All Science Journal Classification (ASJC). In
this system, titles in Scopus are classified under four broad subject clusters (life sciences, physicalsciences, health sciences and social sciences), which are further divided into 27 major subject areas,
which in turn are composed of more granular subcategories. Journals are classified into one ormore of these subcategories based on their content. Journals that are not discipline-specific such as
Nature and Science fall under the classification “multidisciplinary.”
For our analyses, publications in “multidisciplinary” journals were re-classified into the appropriate
subcategories based on the text in their titles and abstracts using Elsevier fingerprinting technology.
Authors were counted towards a subject area/subcategory if more than 30% of their publications
during the period were published in a journal with that classification. Authors who published 30%
or more of their publications in journals classified in multiple subject areas/subcategories will counttowards more than one subject area/subcategory.

PAGE 16 The Researcher Journey Through a Gender Lens

FIGURE 1.3

Physical sciences

More men

1.3

Gender ratio among
active authors during
the period 2014–2018,disaggregated according
to subject area.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Computer
Science

Mathematics

KEY
Argentina
BrazilMexicoPhysics &Astronomy

CanadaUSA
EU28
UK
Portugal

Chemistry

Spain
France
Italy
Netherlands
Denmark
Australia
Japan

Physical Sciences

Germany

ChemicalEngineering

Materials Science

Engineering

EnergyEnvironmental
Science

Earth &
Planetary Sciences

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenResearch Participation PAGE 17

FIGURE 1.3 (CON’T)

More men

1.3

Health and life sciences

Gender ratio among
active authors during
the period 2014–2018,disaggregated according
to subject area.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Agricultural
Sciences

Pharmacology

KEY
BrazilMexicoCanadaUSA

Life Science

Argentina

Neuroscience

EU28
UK
Portugal

Biochemistry

Spain
France
Italy
Netherlands
Germany

Immunology

Denmark
Australia
Japan

Veterinary

Health Sciences

Dentistry

HealthProfessions

Medicine

Nursing

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

PAGE 18 The Researcher Journey Through a Gender Lens

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenFIGURE 1.3 (CON’T)

Social sciences

More men

1.3

Gender ratio among
active authors during
the period 2014–2018,disaggregated according
to subject area.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Psychology

Business

KEY
Argentina
BrazilMexicoUSA
EU28
UK
Portugal
Spain

Social Sciences

Social Sciences

CanadaDecision Sciences

France
Italy
Netherlands
Germany
Denmark

Economics

Australia
Japan
Arts &
Humanities

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More women

FIGURE 1.3 TAKEAWAY:

For most countries, the ratio of women to men is lowest in the physical sciences
and highest in the life and health sciences. Nursing and psychology stand apart withmore women than men in most countries. Japan has the lowest ratio of women tomen in every subject area.

Research Participation PAGE 19

Disaggregating active authors from the period
2014–2018 within each subject area according toyear of first publication, we observed similar trends
as those seen for all researchers in aggregate: there
were more women among authors who started
publishing recently (presumably younger authors)compared to those with a longer publication
history, regardless of subject area (supplemental
data, Figure B.4).
Authorship position can indicate an author’s
contribution to the research in some fields. We
assessed gender balance among active authors in
the position of corresponding author, first author
and last author (as provided by the authors at thetime of publication, as captured in Scopus) over
the two time periods and examined differences ingender balance for each author position comparedto the overall author population.
Across all countries, the population ofcorresponding authors and last authors consistedof slightly more men compared to the total author
population (Figure 1.4). First authors tended tobe similar in gender distribution to the author
population as a whole. To determine what factors
underlie this trend, we assessed the publication
history of authors within each authorship positiongroup. We found that in every country, the total
population of active authors and first authors
mostly consisted of those who first publishedbetween 2014–2018 while corresponding authors
and last authors have been publishing for a longer
time (supplemental data Figure B.5). This suggests
a relationship between authorship position andauthor seniority.

Consistent with the data on all authors, theratio of women to men in these positions(corresponding author, first author and lastauthor) in the 2014–2018 cohort was higher thanin the 1999–2003 cohort, across all countries(supplemental data Figure B.6), suggesting thatdifferences in gender ratio observed over time apply
to authorship positions as well.
When we normalized the ratio of women tomen in specific authorship positions to the ratio
overall, we found that the greatest divergencein ratio based on authorship position occurredin the life sciences and the health sciences(supplemental data Figure B.7). In these fields,
we observed that the ratio of women to men was
lower among corresponding authors comparedto the overall author population and was lower
among last authors compared with corresponding
authors. Immunology stood out in this regard, with
97 women per 100 men overall (median among
countries) compared to only 68 women per 100
men as corresponding authors and 52 women per
100 men as last authors. The ratio of women tomen among first authors was frequently the sameas the overall author ratio. Together, these datasuggest that in these fields, first authors generally
have a shorter publication history and are more
likely to be women, while corresponding and lastauthors generally have a longer publication history
and are less likely to be women. These observations
are consistent with the idea that, in the life sciences
and health sciences, the last author is more likely
to be the lead Principal Investigator (PI) responsible
for securing funding and the first author is more
likely to have less experience and be more junior.
Thus, our results suggest that in the life and healthsciences, the proportion of women among PIs is
low, while the proportion of women among juniorresearchers, though still below parity in mostcountries, is higher.

Men are more highly represented among authors with a long publication history while
women are highly represented among authors
with a short publication history.

PAGE 20 The Researcher Journey Through a Gender Lens

More men

FIGURE 1.4

1.4

Gender ratio among
active authors in 2014–2018 disaggregated basedon author position.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

All Authors

KEY
Argentina
BrazilCorresponding
Authors

MexicoCanadaUSA
EU28First Authors

UK
Portugal
Spain
FranceItaly

Last Authors

Netherlands
Germany
Denmark
Australia
Japan

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More women

FIGURE 1.4 TAKEAWAY:

Last authors and corresponding authors consist of proportionally more men than
women compared with the overall author population in every country.

Research Participation PAGE 21

Case Study:

Gender diversity withinsubfields of medicine
For the subject area-level analyses shown
throughout chapter 1, we assessed the ratio of
women to men within 26 major subject areas.
Because the subject area of medicine is broad andincludes several subfields, we further disaggregatedthe data within the subject area of medicine toprovide insight on gender diversity across thesubfields within medicine. These subfields are
based on a combination of subcategories as
explained in Appendix A, section “Subject areas andsubfields included in the analysis.”
We observed that within the subject area of
medicine, the subfield of fertility & birth saw thegreatest increase in representation of womenamong authors: during the period 1999–2003, themedian ratio among countries was 73 women per
100 men, whereas during the period 2014–2018,the median was 161 women per 100 men (Figure1.5). This increase in the median between periods
was greater than the increase seen in the subject
areas of nursing and psychology (supplemental
data, Figure B.3). Pediatrics saw a similarly large
increase in the proportional representation of
women among active authors, with the medianratio increasing to 150 women per 100 men during
the period 2014–2018, from 75 women per 100 men
during the period 1999–2003.

PAGE 22 The Researcher Journey Through a Gender Lens

Among active authors during the period 2014–2018, the median ratio of women to men among
the countries studied was highest in the subfieldof fertility & birth, followed by pediatrics (Figure
1.5, Figure B.8). The lowest ratio of women to men
was observed in the subfields of surgery followedby cardiology & pulmonology. General clinicalmedicine, cancer and infectious diseases & allergy
had a ratio of women to men that was similar tothe subject area of medicine overall. In all subfieldsof medicine, Japan had the lowest ratio of women
to men while Portugal often had the highest ratioof women to men among authors.
As observed at the country and subject area levels,
we noted a higher ratio of women to men amongauthors with a shorter publication history (Figure
1.6). In many subfields of medicine, the medianratio of women to men was observed to be notably
higher among those who first published in 2004–
2008 compared with authors who first publishedin 2003 or prior. However, in emergency medicine,surgery, radiology & imaging and cardiology &pulmonology, the ratio of women to men increased
more gradually among authors with a shorter
publication history.
Together, these data show that although women’s
representation as authors has increased in all
subfields of medicine analyzed, the pace of change
in emergency medicine, surgery, radiology &imaging and cardiology & pulmonology has lagged
the pace seen in medicine overall. In contrast,
a high pace of change in fertility & birth andpediatrics has resulted in the underrepresentationof men in these subfields.

1.5

FIGURE 1.5

Gender ratio among Argentina
Brazilactive authors during Mexic0
Canadathe period 1999–2003 USA
EU28
and 2014–2018 in the UK
Portugalsubject area of medicineSpainand its subfields. Data France
Italy
Netherlands
for selected subject
Germany
Denmark
areas within the life
Australia
sciences are shown for Japan
comparison.

More men

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Pharmacology

Neuroscience

Immunology &Microbiology

KEY
1999–2003

2014–2018

Argentina
BrazilMexicoBiochemistry

CanadaUSA
EU28
UK
Portugal

Medicine

Spain
France
Italy
Netherlands
Germany

General Clinical
Medicine

Denmark
Australia
Japan
Pediatrics

Emergency
Medicine

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenResearch Participation PAGE 23

More men

FIGURE 1.5 (CONT)

Gender ratio among
active authors during
the period 1999–2003
and 2014–2018 in thesubject area of medicine
and its subfields. Datafor selected subject
areas within the life
sciences are shown forcomparison.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Surgery

Radiology& Imaging

Cardiology& Pulmonology

KEY
1999–2003

2014–2018

Argentina
BrazilMexicoDiabetes& Endocrinology

CanadaUSA
EU28
UK
PortugalCancerSpain
France
Italy
Netherlands
Germany

Fertility& BirthDenmark
Australia
Japan

Infectious
Diseases& Allergy

Public Health

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

PAGE 24 The Researcher Journey Through a Gender Lens

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenFIGURE 1.6

1.6

Gender ratio among
active authors during theperiod 2014–2018 in eachcountry in the subject
area of medicine and its
subfields, grouped basedon year of author’s firstpublication.

More men

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

A

Pharmacology

B
C
D

A

Neuroscience

B
C
D

GROUP

YEAR OF FIRSTPUBLICATION

A

2003 or priorB

2004–2008C

2009–2013D

2014–2018

ArgentinaA

Immunology &Microbiology

A

Biochemistry

B
CD

MexicoCanadaEU28

C
D

BrazilUSA

B

A

Medicine

B
C

UK

D

PortugalA

Spain
France
Italy

General Clinical
Medicine

Netherlands

C
D

GermanyA

Denmark
Australia

B

Pediatrics

Japan

B
C
D

A

Emergency
Medicine

B
C
D

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenResearch Participation PAGE 25

FIGURE 1.6 (CONT)

1.6

Gender ratio among
active authors during theperiod 2014–2018 in eachcountry in the subject
area of medicine and its
subfields, grouped basedon year of author’s firstpublication.

More men

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

A

Surgery

B
C
D

A

Radiology& Imaging

B
C
D

GROUP

YEAR OF FIRSTPUBLICATION

A

2003 or priorB

2004–2008C

2009–2013D

2014–2018

ArgentinaA

Cardiology& Pulmonology

A

Diabetes& Endocrinology

BCD

MexicoCanadaEU28

C
D

BrazilUSA

B

A

CancerB
C

UK

D

PortugalA

Spain
FranceItaly

Infectious
Diseases& Allergy

Netherlands

A

DenmarkJapan

C
D

Germany
Australia

B

Fertility& BirthB
C
D

A

Public Health

B
C
D

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

PAGE 26 The Researcher Journey Through a Gender Lens

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenResearch Participation

Grant Awardees
Assessment of grant awardees provides insight
into the gender composition of those who are
successfully competing for research funding
and contributing to funding agencies’ research
portfolios and missions. Many factors contributeto the composition of grant awardees. The
composition of the available pool of individuals
who are qualified to apply, whether the research
proposed fits the research priorities of the funding
institution, and the quality of the application
itself are just a few such factors. Gender-based
differences may reflect gender differences in who
applies for awards and/or who is awarded.
We assessed the ratio of women to men among
research grant awardees during the period
2014–2018 by examining awards data from Elsevier’s
Funding Institutional solution. Detailed methods
on how awardees were identified are provided in
the Appendix A. Analyses were limited to thosecountries with at least 5,000 awardees for whom agender could be inferred.
Consistent with our findings based on author
data, we observed fewer women awardees thanmen in all awarding countries included in theanalysis (Figure 1.7). Canada had the highest
representation of women among grantees, with
50 women per 100 men awarded a research grant,
while Japan was the furthest from parity with 10
women per 100 men. All other countries and theEU28 in aggregate had a ratio between 25 to 45
women awardees per 100 men. Contrasting thesedata with author data, we noted that the proportionof women among awardees in the USA, EU28, theUK, Germany and Japan was below the ratio seen
for corresponding authors and above the ratio
seen among last authors. This is consistent with
the notion that research awardees are frequently
senior investigators and suggests that the awardee
population closely reflects the pool of available
recipients (i.e., senior investigators). In Canada,
the ratio of women to men among awardees was
slightly higher than the ratio of corresponding
authors (by 5 women per 100 men). One possible
explanation for this could be the presence of
mechanisms in Canada to award research grants
to those who have never been in a leadership
position. In contrast, the gender ratio observed
among grant awardees in Australia was lower than
the ratio of women to men among corresponding
authors (by 21 women per 100 men) and lastauthors (by 6 women per 100 men). This may be
due to different practices in taking the last or
corresponding author position in Australia or it
may indicate gender bias against women in grantaward systems. Alternatively, differences in thegender ratios of grant awardees compared toauthors may reflect differences in the distributionof authors across subject areas compared to the
distribution of awardees across subject areas ineach country. For example, a difference might beseen if a country’s author pool is predominantly
composed of researchers in the health andlife sciences (which is the case for all countries
analyzed) but the awardee pool consists ofproportionally more social and physical scientists(both fields in which the gender ratio among lastand corresponding authors is more similar to theratio for the overall author population).

Research Participation PAGE 27

FIGURE 1.7

More men

1.7

Gender ratio among
research grant awardees
receiving an award
during the period
2014–2018 comparedto author ratios among
all active authors, firstauthors, last authors andcorresponding authors
active during the same
period.

10More women

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

AwardeeAll Authors

Corresponding
Authors

KEY
Canada
USA
EU28
UK

First
Authors

Germany
Australia
Japan
Last
Authors

FIGURE 1.7 TAKEAWAY:

In many countries, theproportion of womenamong grantees closelyreflects the proportionof women amongcorresponding and lastauthors.

PAGE 28 The Researcher Journey Through a Gender Lens

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenResearch Participation

Inventors andPatent Assignees
Individuals submitting patents for research
discoveries are actively turning their research
into practical applications with potential forcommercial value. To understand the proportional
representation of women and men among
inventors (those who contribute to the claims ofa patentable invention) and patent assignees (thesubset of inventors who own intellectual property
rights to patents), we analyzed PATSTAT patent
data for the United States Patent and Trade Office(USPTO) and the European Patent Office (EPO).
Data from the China National Intellectual Property
Administration (CNIPA), Japan Patent Office (JIPO)
and Korean Patent Office (KIPO) were evaluatedbut excluded because too few patents included thecountry of the inventor and because the genderof the inventors could not be inferred accurately
for a sufficient number of inventors to generate arobust data set using the approach employed inthis report. Individuals included in this analysis
are those who appeared as inventors or assignees
in any patent applications filed in 1999–2003 or
2012–2016 at either the USPTO or EPO, regardlessof when the patent was granted. We assessedpatents from 2012 to 2016 rather than from 2014
to 2018 because patent applications must first be
published before they appear in PATSTAT, resulting
in a lag of up to 18 months for the EPO. The
methods employed to select these patent offices
and to assign inventors and assignees to a country
are described in more detail in the Appendix
A. Briefly, inventors or assignees were counted
towards a country’s count if more than 30% of theirpatents during the period indicated that country
as the inventor or assignee country. We limited
this analysis to countries with a minimum of 1,400
inventors for whom a gender could be inferred.

In all countries studied, women inventors
represented a small minority of inventors. Spain
had the highest ratio of women to men among
inventors during the period 1999–2003, with 17
women per 100 men, placing it above France (15women per 100 men) and Brazil (14 women per
100 men; Figure 1.8). The ratio of women to men
among inventors in the EU28 was 9 per 100 men,reflecting the relatively lower ratios observed in
the UK (9 women per 100 men) and Germany (6women per 100 men). With only 5 women per 100
men, Japan had the lowest proportion of womenamong inventors across all countries. All countries
showed an increase in the ratio of women to men
among inventors in 2012–2016 compared with
1999–2003, with the exception of Canada, in which
the ratio was stable. The largest increases in ratio
between the two time periods were seen in Mexico(16 women per 100 men, up from 9 women per
100 men) and Spain (24 women per 100 men, up
from 17 women per 100 men). Spain maintained its
rank from the 1999–2003 period, followed by bothFrance and Brazil (17 women per 100 men), Mexico(16 women per 100 men) and Italy (15 women per
100 men). The ratio of women to men among
inventors in the EU28 increased in 2012–2016 to 12
women per 100 men, up from 9 women per 100
men in 1999–2003.
Large gaps between the ratio for assignees andinventors may indicate a loss of intellectual
property (IP), as inventors do not hold the rights(and thus lose the market value) of their inventions.
We observed that, for the majority of countries
analyzed, the ratio of women to men among patentassignees mirrored the ratio observed for inventors(Figure 1.8). Spain, Brazil and Mexico stood apartin that there were fewer women per 100 men
among assignees than among inventors (7 fewer
women per 100 men among assignees compared
to inventors in Spain, 4 fewer in Brazil and 3 fewer
in Mexico).

Research Participation PAGE 29

More men

FIGURE 1.8

1.8

Gender ratio among
inventors and assignees
during the periods
1999–2003 and 2012–2016 for each country
and the EU28.

0

Men per 100 women∞ 1000 500 333 250 200 167

MexicoBrazilCanadaUSA

KEY
1999–2003
2012–2016

EU28

The ratio of women tomen among inventors
and assignees is very low
compared to the ratio
observed for authors andgrantees. Most countries
show very modest changes
in these ratios over time.
Spain and Mexico standapart for having thelargest increases in the
proportion of womenamong inventors.

30

40

50

60

70

80

90

More women

143 125

111

100

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Assignee
Inventor

Assignee
Inventor

Assignee
Inventor

Assignee
Inventor

Assignee
Inventor

Inventor

Spain

France

Italy

Netherlands

Germany

Denmark

Australia

Japan

Assignee
Inventor

Assignee
Inventor

Assignee
Inventor

Assignee
Inventor

Assignee
Inventor

Assignee
Inventor

Assignee
Inventor

Assignee
Inventor

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

PAGE 30 The Researcher Journey Through a Gender Lens

20

AssigneeUK

FIGURE 1.8 TAKEAWAY:

10

Parity between men and women

Women per 100 men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenResearch Participation

Conclusion
Overall, our analysis reveals
incremental improvements in women’s
representation among researchers
along three of the key core activities thatthey undertake: authoring publications,securing research funding and applying
for patents. The rate and magnitude bywhich the gender gap has decreased
within these activities differs acrosscountries and the EU28. Among authors,differences in the ratios of women tomen researchers are observed acrosssubject areas, with a lower representationof women observed in the physicalsciences. Notably, the lower proportionof women in the physical sciences may
in part explain the lower representationof women among patent applicants,
given that patenting activity is higher
in physical sciences subject areas. In
nursing and psychology, the gender gap
has increased as men’s representation

has decreased over time in thesefields. Beyond country/region andsubject area-based differences, we also
observed differences in the proportional
representation of women and men that
correlated with author publication history
and authorship position. The largest
gender gap is observed among authors
with a long publication history and those
who have authored as correspondingor last authors. These insights offer
good context for Chapter 2, in which
we provide further information on men
and women in the world of research byexamining their research footprint interms of publications, grants, patents andcitation impact.

Chapter 2

Research 			Footprint
Measuring the research footprintof women and men

Key Findings• In every country, on average, women researchers
author fewer publications than men, regardless ofauthorship position. The least difference is observed
among first authors while the biggest difference isobserved among all authors.
• Among first authors, the average FWCI of men ishigher than that of women, suggesting gender bias
in citation practice.
• Among grantees, on average, men tend to win moregrants than women.
• Among inventors, men tend to apply for more
patents than women. This difference in average
number of patents applied for by men compared to
women is greater among assignees.

Research Footprint PAGE 33

Research Footprint

Introduction
Ensuring that the research workforce is diverse
is an important first step to ensuring diverse
perspectives are reflected in and informresearch. Active engagement by participantsfrom that workforce across a range of research
activities—publishing, applying for funding
and seeking patents—is also critical. Here, we
examine the outcomes of these research activities,
which form a researcher’s “footprint” and havea significant impact on both the researcher’s
career and the resulting research portfolio overall.
Understanding whether gender-associateddifferences in the researcher footprint exist offers
the opportunity to reflect on potential causes ofgender gaps, likely obstacles that prevent both
men and women to thrive equally and the possible
biases that affect success. Such insights are
crucial to a more comprehensive understandingof the global research environment, enabling anevidence-based approach towards achieving equal
opportunities for all researchers regardless ofgender and for the research enterprise to reap the
benefits of a diverse workforce.

Research publications are an important research
output. They are a means of communicating
research findings to the academic community.
Several studies have described gender disparity interms of scholarly output—the number of articles,
reviews, and abstracts—published by men andwomen researchers, showing that, on average,
women author fewer publications than men, withdifferences in scholarly output varying by subject
area, geography, journal type and authorship
position.14 Citations of research publications area means of crediting the originators of an idea
or finding, as well as recognizing expertise. The
number of citations received by a publication isindicative of uptake of knowledge15 and can serve asa proxy for the academic impact of the publication.
Several studies have noted a gender difference in
how citations accrue, with work authored by womencited less often than that by men, and variationsin the citation gap across subject areas16 andauthorship position17 that may be related to genderbased differences in self-citation and journal
prestige.18 The gender gap in scholarly output and

14 Charlesworth, T., & Banaji, M. (2019). Gender in science, technology, engineering, and mathematics. Journal of Neuroscience, 39(37), 7228-7243. doi: 10.1523/JNEUROSCI.0475-18.2019; Shen, Y., Webster, J.,
Shoda, Y., & Fine, I. (2018). Persistent underrepresentation of women’s science in high profile journals. bioRxiv preprint. 2018. Retrieved from: https://doi.org/10.1101/275362. Accessed October 28, 2019; Elsevier.
(2017). Gender in the Global Research Landscape. Retrieved from: https://www.elsevier.com/research-intelligence/campaigns/gender-17. Accessed October 23, 2019; Bendels, M., Muller, R., Brueggmann, D., &Groneberg, D. (2018). Gender disparities in high-quality research revealed by Nature index journals. PLoS ONE, 13(1). doi: 10.1371/journal.pone.0189136; Lariviere, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto,
C. R. (2013). Global gender disparities in science. Nature, 504(7479), 211-213. doi: 10.1038/504211a; West, J. D., Jacquet, J., King, M. M., Correll, S. J., & Bergstrom, C. T. (2013). The role of gender in scholarly
authorship. PLoS One, 8(7), e66212. doi: 10.1371/journal.pone.0066212; González-Álvarez, J., & Cervera-Crespo, T. (2017). Research production in high-impact journals of contemporary neuroscience: a genderanalysis. Journal of Informetrics, 11(1), 232–243. doi: 10.1016/j.joi.2016.12.007; Filardo, G., da Graca, B., Sass, D. M., Pollock, B. D., Smith, E. B., & Martinez, M. A.-M. (2016). Trends and comparison of female firstauthorship in high impact medical journals: observational study (1994-2014). BMJ, 352, i847. doi: 10.1136/bmj.i847
15 Dion, M. L., Sumner, J. L., & Mitchell, S. M. (2018). Gendered citation patterns across political science and social science methodology fields. Political Analysis, 26(3), 312–327. doi: 10.7910/DVN/R7AQT1
16 Andersen, J. P., & Nielsen, M. W. (2018). Google Scholar and Web of Science: Examining gender differences in citation coverage across five scientific disciplines. Journal of Informetrics, 12(3), 950–959. doi:
10.1016/j.joi.2018.07.010
17 Lariviere, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto, C. R. (2013). Global gender disparities in science. Nature, 504(7479), 211-213. doi: 10.1038/504211a; West, J. D., Jacquet, J., King, M. M., Correll, S. J., &Bergstrom, C. T. (2013). The role of gender in scholarly authorship. PLoS One, 8(7), e66212. doi: 10.1371/journal.pone.0066212; González-Álvarez, J., & Cervera-Crespo, T. (2017). Research production in high-impact
journals of contemporary neuroscience: A gender analysis. Journal of Informetrics, 11(1), 232–243. doi: 10.1016/j.joi.2016.12.007; Filardo, G., da Graca, B., Sass, D. M., Pollock, B. D., Smith, E. B., & Martinez, M.
A.-M. (2016). Trends and comparison of female first authorship in high impact medical journals: observational study (1994-2014). BMJ, 352, i847. doi: 10.1136/bmj.i847
18 Andersen, J. P., Schneider, J. W., Jagsi, R., & Nielsen, M. W. (2019). Gender variations in citation distributions in medicine are very small and due to self-citation and journal prestige. ELife, 8, 1–17. doi: 10.7554/
elife.45374; King, M. M., Bergstrom, C. T., Correll, S. J., Jacquet, J., & West, J. D. (2017). Men set their own cites high: gender and self-citation across fields and over time. Socius, 3. doi: 10.1177/2378023117738903

PAGE 34 The Researcher Journey Through a Gender Lens

citation accrual has been attributed to various
factors. Recent studies have described a “Matilda
effect”—the perception that the scholarly work of
women is lower quality than that of men—whichleads to fewer citations or invitations to collaborateand has a negative effect on future scholarly
output.19 Women are also more likely than men to
take career breaks or switch to a part-time position
to achieve work-life balance or care for a family
member; these breaks can reduce productivity.20
Successfully publishing again after returning toresearch can be difficult, particularly if institutional
support structures are lacking. As publication
output is often used to measure performance inacademic research, gender-based differences in thenumber of publications, as well as the impact of
those publications, can have a significant effect on
the career progression of women researchers.21

Like research publications, patents are an
important outcome of research. Through patents,
researchers claim the rights to the applicationof intellectual property. However, similar tothe observation for publication output, there isevidence that women have a lower patent counts
than men.26
In this chapter, we expand on the body of literature
related to the gender gap in research footprint,
using advanced methodologies to examine theaverage number of publications, grant awards andpatents, as well as the impact of publications asmeasured by citations, across 15 countries and theEU28, overall and in 26 subject areas.

Gender disparities have also been noted in termsof research funding, another benchmark ofsuccess for researchers that factors into tenure
and promotion decisions.22 A recent study foundthat a smaller percentage of women than men
who apply for high-risk, high-reward awards at the
National Institutes of Health (NIH) in the UnitedStates go on to win these awards.23 Another study
reported significant gender differences in thesize of awards to first-time NIH grant awardees,
particularly for the highest-funded grant types.24
Top prizes in science, such as those awarded byprofessional societies, are won more often by men,
who also receive more money and prestige as aresult of winning.25

19 Knobloch-Westerwick, S., Glynn, C. J., & Huge, M. (2013). The Matilda effect in science communication: an experiment on gender bias in publication quality perceptions and collaboration interest. Sci Comm,35(5). doi: 10.1177/1075547012472684; Knobloch-Westerwick, S., & Glynn, C. J. (2013). The Matilda effect—role congruity effects on scholarly communication: a citation analysis of Communication Research andJournal of Communication articles. Communication Research, 40(1). doi: 10.1177/0093650211418339
20 Hunter, L., & Leahey, E. (2010). Parenting and research productivity: new evidence and methods. Social Studies Science, 40(3), 433-451. doi: 10.1177/0306312709358472; Cech, E., & Blair-Loy, M. (2019). Thechanging career trajectories of new parents in STEM. Proceedings of the National Academy of Sciences, 116(10), 4182-4187. doi: 10.1073/pnas.1810862116
21 Nielsen, M. W. (2018). Scientific performance assessments through a gender lens: A case study on evaluation and selection practices in academia. Science and Technology Studies, 31(1), 2–30. Retrieved from:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044744269&partnerID=40&md5=3be6af0abf4427d9a4f778d9ab50bdc2. Accessed October 28, 2019; Van den Besselaar, P., & Sandström, U. (2016). Genderdifferences in research performance and its impact on careers: a longitudinal case study. Scientometrics, 106, 143–162. doi: 10.1007/s11192-015-1775-3
22 Science, D., Draux, H., & Kundu, S. (2018). Gender Imbalance in Cancer Research Grants. Report, (November). Retrieved from: https://doi.org/10.6084/m9.figshare.7378001.v1. Accessed October 28, 2019.; van derLee, R., & Ellemers, N. (2015). Gender contributes to personal research funding success in The Netherlands. Proceedings of the National Academy of Sciences, 112(40). doi: 10.1073/pnas.1510159112
23 Wadman, M. (2019). NIH marquee awards for ‘high risk, high reward’ projects skew male—again. Science, October 9. https://doi.org/10.1126/science.aaz7967. Accessed October 28, 2019.
24 Oliveira, D. F. M., Ma, Y., Woodruff, T. K., & Uzzi, B. (2019). Comparison of National Institutes of Health grant amounts to first-time male and female principal investigators. Journal of the American Medical
Association, 321(9), 898-900. doi: 10.1001/jama.2018.21944
25 Ma, Y., Oliveira, D. F. M., Woodruff, T. K., & Uzzi, B. (2019). Women who win prizes get less money and prestige. Nature, 565(7739), 287-288. doi: 10.1038/d41586-019-00091-3
26 Whittington, K. B., & Smith-Doerr, L. (2008). Women inventors in context: disparities in patenting across academia and industry. Gender & Society, 22(2), 194-218. Retrieved from https://doi.
org/10.1177/0891243207313928. Accessed December 3, 2019.

Research Footprint PAGE 35

Research Footprint

Author Publication Output
In this section, we assessed the average
number of publications that were authored by
women and men. We calculated the average
number of publications for each gender by
first counting the number of publications byeach author and then determining the average
across authors of the same gender. To get asense of authors’ output as both contributing
authors and as lead authors, we assessedauthors based on authorship position andcalculated the average output among authors
who have been in: 1) any authorship position,2) the corresponding author position, 3) the
first author position and 4) the last author
position. Publications in which authors arelisted in alphabetical order and publications
with two or fewer authors were not included
among the counts of first and last author
papers. We limited the analysis to output during

PAGE 36 The Researcher Journey Through a Gender Lens

a five-year period: the publication output
during the period 1999–2003 was assessed forauthors who were active during those same
years and the publication output during theperiod 2014–2018 was assessed for authors
who were active during those years. Authors
were considered active if they published at least
two publications during the defined period ofinterest. To avoid excluding “new authors,” thatis, those authors who first published during theperiod of interest, we applied different criteria
for inclusion of these authors. “New authors”
were included in the 1999–2003 cohort if they
subsequently published within five years of
their first publication. “New authors” whose
first publication appeared during the period
2014–2018 were unconditionally included in
the 2014–2018 cohort. Detailed methods areavailable in Appendix A.

Our data show that, on average, women publishedless than men in a five-year period in every
country assessed, regardless of authorship
position (Figure 2.1, supplemental data Table
B.2). The same trends were observed for authors
active during the period 1999–2003 (supplemental
data Table B.2). The average publication count
was most similar between women and men
for first author publications, ranging from nodifference in the average publication output by
men compared to women in the Netherlands to
1.3 times more publications by men comparedwith women in Japan. The greatest differencein average publication output was seen among
those in any authorship position, with men on
average authoring 1.5 times more publications
than women in 11 of the 15 countries (along with
the EU28 as a whole). The difference in publication
output among those in last author position
ranged from 1.1 times more (i.e., 10% more) on
average by men than women in Argentina to 1.7
times more by men than women in Japan. The
difference in publication output among those
who were corresponding authors ranged from 1.2
times more on average by men than women in
Argentina, Portugal, the Netherlands and Brazil
to 1.5 times more by men than women in Japan.
Argentina stood out for having the least difference
between men and women in publication output

across various authorship positions, while Japan
stood out for having the greatest difference inpublication output among first authors, lastauthors and corresponding authors. This suggests
a relationship between gender ratio and genderrelated differences in publication output. When we
assessed whether there was a correlation between
the gender ratio among authors and the ratio of
average output among countries, we observed aslight correlation among corresponding authors (R2= 0.69; p < 0.0001; supplemental data Figure B.9).
To assess the role of author publication history
in contributing to the difference in publication
output of men compared with women, wedisaggregated the authors based on the yearof first publication. We observed that, for mostcountries, the gender related difference inpublication output was higher among authors witha longer publication history and minimal amongauthors with the shortest publication history(supplemental data Figure B.10). This trend wasmost apparent among all authors but also observed
among last authors and corresponding authors.
Among those who published as first authors,
the greatest difference in publication output wasobserved among authors whose first publication
was published in the period 2009–2013.

In every country, on average, women researchers
author fewer publications than men, regardlessof authorship position. The least difference in the
average number of publications by women compared
to men is observed among first authors and thebiggest difference is observed among all authors.

Research Footprint PAGE 37

Men publish more

FIGURE 2.1

2.1

Ratio of the average
Argentina
number of publications Brazil
Mexic0by women to men and CanadaUSAEU28
men to women, asUKshown. Data are based Portugal
Spain
on average number of France
publications by active Italy
Netherlands
authors in the period Germany
Denmark
Australia
2014–2018 in eachJapancountry, disaggregatedaccording to author
position.

Women to men 0.50
Men to women

2.0

Parity between men and women

0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91
1.9

1.8

1.7

1.6

1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

Women publish more

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50

All Authors

Corresponding
Authors

First
Authors

Argentina
BrazilMexicoLast
Authors

CanadaUSA
EU28

Women to men 0.50

UK

Men to women

Portugal

2.0

0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91
1.9

1.8

Men publish more

1.7

1.6

1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

FranceNetherlands
Germany
Denmark
Australia
Japan

PAGE 38 The Researcher Journey Through a Gender Lens

2.0

Women publish more

Spain
Italy

1.9

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50

FIGURE 2.1 TAKEAWAY:

On average, women author fewer publications than men, regardless of authorship
position. The least difference in the average number of publications by womencompared to men is observed among first authors and the biggest difference isobserved among all authors.

When disaggregating the data by subject area,
we observed that, within most subject areas,
the difference in publication output between
women and men mirrored the pattern seen for
all research in aggregate: the greatest differencein output of men compared to women was seenamong all authors in any position, followed bythose in last and corresponding author positions,and the least difference was seen among firstauthors. Author publication history appeared to
explain part of the difference observed among
last and corresponding authors, as the differencein output was greatly diminished when the data
were disaggregated by subject area and publication
history. However, when assessing output of all
authors (i.e., regardless of authorship position),
we observed that, in the life sciences and healthsciences, a large gender gap in publication
output persists among authors with the longest
publication history. This may be due in part tothe broad range of years included in this group(all authors whose first publication was in 2003 orprior). If the first year of publication among most
women in this group was more recent than the firstyear of publication among most men in this group,
this difference in publication history could accountfor the difference in publication count. Further
statistical analyses would provide greater clarity
on the relationship between gender differencesin publication output and author country, subject
area, publication history and authorship position.

From the available data, it wasn’t possible todirectly assess whether a difference in childcare responsibilities among men and womencontributed to the observed gender differencein publication output. We could not identify any
studies that document when most authors havechildren relative to their first publication. We
hypothesized that a substantial population of postdoctoral researchers who have young children may
be represented among the first author researchers
who first published in 2009–2013 in the life andhealth sciences. Additional family responsibilities
that more often fall to women, including taking
time off for pregnancy and childcare, may have
led to a decrease in research activity and a lower
publication output among women in this group.27
However, further sociological data are required
to make a definitive link. The data do, however,suggest a relationship between the gender gap
in publication output and publication history,
particularly among those in any authorship
position, which suggests that gender differencesin networking and collaborations may drive thisdifference. Consistent with this, our 2019 surveyof the global research community (described inAppendix A) found that, on average, men report thatthey are invited to collaborate on a research projectthat could lead to a publication more often than
women (mean number of invitations to collaborate/
year: men = 3.52, women = 3.04; Appendix A, FigureC.4). This suggests that men may have greater
opportunities than women to be named as a coauthor. We explore the role of women and men’sco-author networks further in Chapter 4.

27 Fox, M. F. (2005). Gender, family characteristics, and publication productivity among scientists. Social Studies of Science, 35(1), 131-150. doi: 10.1177/0306312705046630; Hunter, L. A. & Leahey E. (2010). Parenting
and research productivity: new evidence and methods. Social Studies of Science, 40(3), 433-451. doi: 10.1177/0306312709358472; Kyvik, S. (1990). Motherhood and scientific productivity. Social Studies of Science,
20, 149-160. doi: 10.1177/030631290020001005; Kyvik, S. & Teigen M. (1996). Child care, research collaboration, and gender differences in scientific productivity. Science, Technology and Human Values, 21(1),54-71. doi: 10.1177/016224399602100103; Long, J. S. (1990). The origins of sex differences in science. Social Forces, 68(4), 1297-1315. doi: 10.1093/sf/68.4.1297; Stack, S. (2004). Gender, children and research
productivity. Research in Higher Education, 45(8), 891-920. doi: 10.1007/s11162-004-5953-z; Miller, S. (2019). To improve gender equality, help men take parental leave. Society for Human Resource Management.
Retrieved from https://www.shrm.org/resourcesandtools/hr-topics/benefits/pages/help-men-take-parental-leave.aspx. Accessed December 3, 2019.; Cerrato, J., & Cifre, E. (2018). Gender inequality in householdchores and work-family conflict. Frontiers in Psychology, 9, 1330. doi: 10.3389/fpsyg.2018.01330; Pew Research Center. (2015). Raising Kids and Running a Household: How Working Parents Share the Load.
November 4. Retrieved from https://www.pewsocialtrends.org/2015/11/04/raising-kids-and-running-a-household-how-working-parents-share-the-load/. Accessed December 3, 2019.; Bianchi, S. (2011). Familychange and time allocation in American families. Annals of the American Academy of Political and Social Science, 638(1), 21-44. doi: 10.1177/0002716211413731

Research Footprint PAGE 39

Research Footprint

Field-Weighted
Citation Impact
Citations accrued by publications can provide
insight into the academic impact of publications,as researchers cite each other’s work to signalthat they are further building on that work. We
used a field-weighted metric in which citation
count is normalized to account for the publication
type, publication year and subject area because
these three variables greatly impact the accrualof citations by a publication. This metric, fieldweighted citation impact (FWCI), was calculated
for each publication. To compare average FWCI
for women and men, we first calculated themean FWCI for each active author based on their
publications during the five-year period 2014–2018
and then calculated the mean for each gender
based on the author-level average FWCI (detailed
methods are available in Appendix A). Different
factors can influence whether research is cited. We
expected that if differences in how publications
were cited are related to the gender of the authorsof the article, these differences would be mostapparent when assessing based on the gender ofthe first author, last author and/or corresponding
author.
Our analyses revealed that, among the countries
studied, the average FWCI for men compared to
women when assessing all authors, regardless ofauthorship position, was close to equivalent in all
countries and the EU28, with a ratio of FWCI for
men to women that ranged from 0.96 in the UK
to 1.04 in Argentina, and a median of 1.01 among
countries studied (Figure 2.2, supplemental data
Table B.3). The difference between average FWCI

among men and women was slightly higher whenassessing last authors and ranged from a ratio of
0.97 in Argentina to 1.12 in Portugal, with a medianratio of 1.05 among the countries studied. The
trend among last authors was similar to that ofcorresponding authors (ratio of average FWCI ofmen to that of women ranged from 1.01 in Mexico
to 1.14 in France, with a median of 1.06 among
countries). The greatest difference in average
FWCI was observed among first authors. Among
first authors, men’s average FWCI was greaterthan women’s by 1.1 times or more in 12 of the 15
countries studied along with the EU28. Together,
this suggests that gender influences citation
behavior on the basis of authorship position,
particularly among first authors. Among active
authors during the period 1999–2003, we observedthat the ratio of average FWCI was closer to parity
among first and last authors but not corresponding
authors, suggesting that for some author positions,gender differences in how research is cited
decreases as research becomes older (supplemental
data Table B.3). Overall, and consistent with theprevious Elsevier analysis,28 differences in FWCI of
publications by men and women remained small. It
has been suggested that self-citations and journal
prestige may play a role in this discrepancy, as has
been observed in the field of medicine.29

28 Elsevier. (2017). Gender in the Global Research Landscape. Retrieved from: www.elsevier.com/research-intelligence/campaigns/gender-17. Accessed October 23, 2019.
29 Anders, J. P., Schneider, J. W., Jagsi, R., & Nielsen, M. W. (2019). Meta-research: gender variations in citation distributions in medicine are very small and due to self-citation and journal prestige. eLife, 8, e45374.
doi: 10.7554/eLife.45374

PAGE 40 The Researcher Journey Through a Gender Lens

Men are cited more

FIGURE 2.2

2.2

Argentina
Ratio of the average
BrazilFWCI of publications Mexic0
Canadaby women to men and USA
EU28
men to women, asUKshown. Data are based Portugal
Spainon publications by activeFrance
Italy
Netherlands
authors during theGermany
period 2014–2018 in eachDenmark
Australia
country, disaggregated Japanaccording to author
position.

Parity between men and women

Women to men

0.50 0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91

Men to women

2.0

1.9

1.8

1.7

1.6

1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

Women are cited more

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50

All Authors

Corresponding
Authors

First
Authors

Argentina
BrazilMexicoCanadaLast
Authors

USA
EU28
UK
Portugal
Spain

Women to men

0.50 0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91

Men to women

2.0

1.9

1.8

1.7

Men are cited more

1.6

1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50
Women are cited more

France
Italy
Netherlands

FIGURE 2.2 TAKEAWAY:

Germany

Among first authors, the average FWCI of men is higher than that of women,suggesting gender bias in citation practice.

Denmark
Australia
Japan

Research Footprint PAGE 41

Research Footprint

Grants Awarded
The number of research grants awarded toresearchers can vary depending on the number of
proposals submitted, the quality of a researcher’s
grant proposals and the track record of theresearcher. However, there are other factorsthat can also influence whether a researcher isawarded a grant. For example, researchers may
be awarded more grants if they lead a large
research group or if they frequently collaborate
with researchers who have a high award successrate. Biases in awarding systems can impact both
who receives grant awards and how many awards
and award dollars are received. In this section, we
assessed the average number of awards received
by individuals in each country and the EU28.
Figure 2.3 (supplemental data Table B.4) shows

FIGURE 2.3

the average number of awards granted to womencompared to men during the period 2014–2018. In
Japan and the EU28, the average number of grants
awarded to women and men was almost equal.
The observation of near parity for grants received
by women and men in Japan contrasts with thevery low ratio of women to men awardees inJapan shown in Figure 1.7. Canada had the highest
proportion of women among awardees and saw
the largest gender-based difference in average
number of awards received: men in Canada wereawarded 1.4 times (40%) more grants than women.
In all other countries, the average number ofawards received by men was 1.1–1.2 times greaterthan the average received by women.

Men are awarded more

2.3

Ratio of the average
Argentina
number of research
BrazilMexic0
grants received by
CanadaUSA
women to men andEU28
men to women in each UK
PortugalSpaincountry during the period
France2014–2018.
Italy
Netherlands
Germany

Parity between men and women

Women to men

0.50 0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91

Men to women

2.0

1.9

1.8

1.7

1.6

1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

Women are awarded more

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50

Research grants
received

Women to men

0.50 0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91

Men to women

2.0

1.9

1.8

1.7

Men are awarded more

1.6

1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50
Women are awarded more

Denmark

CanadaAustralia
Japan

USA
EU28
UK
Germany
Australia
Japan

PAGE 42 The Researcher Journey Through a Gender Lens

Among grantees, on average, men
tend to win more grants than women.

Research Footprint

Number of
Patent Applications
Various factors can influence whether individuals
apply for patents. In addition to having an
invention that is suitable for patenting, individuals
are more likely to apply for a patent if they havesupport throughout the patenting process,are aware of what support is available and areencouraged to apply. We determined the numberof patent applications from individual inventors(those who contribute to the claims of a patentable
invention) and assignees (the subset of inventors
who own intellectual property rights to patents),
and calculated the average number of patentapplications across men and women from eachcountry and the EU28.

During the period 2012–2016, women inventors
and assignees appearing on European Patent
Office (EPO) and United States Patent andTrade Office (USPTO) patent applications were
contributors on fewer patent applications thanmen on average in every country and the EU28
(Figure 2.4; supplemental data Table B.5). Among
inventors, the average number of patents that
men applied for ranged from 1.1 times morethan women (in Italy, Spain and Denmark) to 1.5
times more than women (in Japan). Among thecountries studied, the median ratio of the average
number of patent applications by men compared
to women was 1.2. The trend for assignees was
slightly higher, with a median ratio of 1.4 among
the countries studied. Italy was at the lowest end,
with no difference in the average number of patentapplications by men and women assignees. The
greatest difference in the average number of patentapplications by men compared to women assignees
was seen for the Netherlands (on average, men
applied for 3.1 times more patents than women).
Along with the Netherlands, France and Japan
were far above the median, with men assignees inthese countries applying for 2.4 and 2.1 times more
patents, respectively, than women.

Research Footprint PAGE 43

Overall, the trends seen for the average number ofpatent applications by women and men inventors
and assignees during the period 2012–2016
were similar to those observed for the period
1999–2003 (supplemental data Table B.5). Assessing
assignees, the median ratio for average number
of applications by men compared to womenamong countries was 1.5 in 1999–2003 and 1.4 in2012–2016. Among inventors, the median ratio
among countries studied was slightly greater in
2012–2016 (at 1.2) compared with 1999–2003 (at1.1). Unlike what was observed for 2012–2016, there
were a few countries in 1999–2003 in which women
inventors applied for slightly more patents on
average than men. Australia stood apart from othercountries in 1999–2003 in that, among assignees,
women applied for 2.6 times more patents thanmen, and among inventors, women applied for 1.3
times more patents than men. This higher averageapplication count for women in Australia was notseen in 2012–2016.

When comparing the data on the average
number of patent applications submitted withthe data on the number of women and men
among inventors, we observed that, in manycases, countries with a lower proportion of
women among inventors (Japan, Germany and theNetherlands) also had the greatest difference inthe average number of applications, with women
applying for far fewer applications than men.
This was similar to the relationship observed forauthors and publication output. However, we
did not find any correlation between the ratio of
women to men among inventors compared withthe ratio of average number of patent applications
by women and men (R 2 = 0.25; p = 0.08). The
inclusion of more countries in the dataset may
reveal a more robust relationship.

Men applied for more

FIGURE 2.4

2.4

Argentina
Ratio of the average
Brazilnumber of patent
Mexic0
Canadaapplications by women USA
EU28
to men and men toUK
women in each country Portugal
Spain
Franceduring the period
Italy
Netherlands
2014–2018.
Germany

Parity between men and women

Women to men 0.29 0.31 0.33 0.36 0.40 0.44 0.50 0.57 0.66 0.80
Men to women

3.5 3.25 3.0 2.75 2.5 2.25 2.0 1.75 1.5 1.25

1.0

Women applied for more

1.25 1.5 1.75 2.0 2.25 2.5 2.75 3.0 3.25 3.5
0.80 0.66 0.57 0.50 0.44 0.40 0.36 0.33 0.31 0.29

Inventor

Assignee

Denmark
Australia

BrazilJapan

MexicoCanada

Women to men 0.29 0.31 0.33 0.36 0.40 0.44 0.50 0.57 0.66 0.80
Men to women

3.5 3.25 3.0 2.75 2.5 2.25 2.0 1.75 1.5 1.25
Men applied for more

1.0

1.25 1.5 1.75 2.0 2.25 2.5 2.75 3.0 3.25 3.5
0.80 0.66 0.57 0.50 0.44 0.40 0.36 0.33 0.31 0.29
Women applied for more

USA
EU28
UK
Spain
France
Italy
Netherlands
Germany
Denmark
Australia
Japan

PAGE 44 The Researcher Journey Through a Gender Lens

Among inventors, men tend to apply
for more patents than women. Thisdifference is greater among assignees.

Case Study:

Assessing gender balanceamong China’s authors
The methods for inferring author gender in thisreport were based on author names as they are
written using the Roman alphabet. However, thisapproach delivered poor results for authors from
China: we did not obtain gender approximation
for a sufficient number of authors to pass thesame thresholds applied to other countries
included in the report. We found that the genderdisambiguation methods used could be morereliably applied to author names written in
Mandarin than to those same names transliteratedusing the Roman alphabet. This is because
Mandarin is a tonal language: a name spelled in
the same way using the Roman alphabet can bespelled and pronounced differently using Chinesecharacters, with some versions referring to names
associated with men and others referring to names
associated with women. Recently, efforts have been
made to include alternate non-Roman text names
for authors whose names are written in a text otherthan the Roman alphabet in the author byline.
We capitalized on these efforts and retrieved thenames of authors that had submitted their namein Mandarin. This typically occurs in Mandarin
language journals. For this case study analysis, we
assessed statistics related to authors who provided

a Mandarin name for any publication during theperiod 2014–2016 because Mandarin language
author names have only been collected for thisperiod thus far. We then inferred the gender ofthese authors using NamSor and used the authors’
Scopus author profiles to identify their publication
history and output. We used a threshold for the
Gender Probability Score that was lower than thescore used elsewhere in this report to increase therecall and ensure a sufficient number of authors foranalysis. Detailed methods on how this cohort ofauthors were defined and their gender was inferred
are available in Appendix A, section “Analysis ofauthors for case study on China.”
A total of 76,627 active authors with a Mandarin
name were identified using this approach. Of
those authors, 8,019 (10.5%) were predictedby NamSor to be women, 23,131 (30.2%) werepredicted to be men and the gender of theremaining 45,477 (59.4%) could not be determined.
Our approach in the following analyses was basedon the assumption that the authors of unknown
gender were distributed among men and womenaccording to the same distribution observed for
those for whom gender could be predicted.

Research Footprint PAGE 45

Our analysis revealed that the ratio of women tomen in this cohort was 0.34, meaning that there
were 34 women per 100 men in the group (Figure2.5). We assigned authors to subject areas basedon their publication record during the period
2014–2018: authors were assigned to a subject
area if at least 30% of their publications were ina journal within that subject area. The majorityof authors in the cohort were in the physicalsciences, particularly engineering (51% of authors),materials science (24% of authors) and physics &astronomy (22% of authors). Note that becausesome journals are categorized under more than
one subject area, authors could be assigned tomultiple subject areas. However, even consideringthat some authors counted towards multiple
categories, the representation of authors in thephysical sciences was higher than expected basedon China’s publication output across all subject
areas. This was likely due to sampling bias. That is,
the set of authors whose names were available in
Mandarin for this study were not a representative
sample of all authors in China and authors fromthe life sciences, health sciences and social scienceswere underrepresented in the cohort. This highrepresentation of authors from three subject areasin this cohort should be considered when assessing
statistics provided at the level of “all subject areas,”and data at this level should not be assumed torepresent China’s entire research workforce. Hence,
results from this case study need to be interpretedwith care and should not be compared directly withfindings from other countries reported on here.

Disaggregating this cohort of authors based on
their publication history resulted in similar trends
seen for other countries, in that the group of
authors with the shortest publication history (groupD, first publication in 2014) was closer to gender
parity than the group of authors with the longest
publication history (group A, first publication in2003 or prior; Figure 2.6).
As observed for other countries, women in thiscohort of authors published fewer publications
than men within the five-year period of 2014–2018(Figure 2.7). This difference in publication output
was greatest among those with the longest
publication history and decreased among thosewith shorter publication histories. One possible
reason for this difference could be that, among
those with a longer publication history, men
had more collaborations, resulting in a higher
publication count than women. Time taken off
by women due to childcare, eldercare and otherfamily care responsibilities may also account forthe difference in publication count.30

30 Cook, S. (2013). Women’s paid work and unpaid care responsibilities in China. A Planet For Life. Retrieved from http://regardssurlaterre.com/en/womens-paid-work-and-unpaid-care-responsibilities-china.
Accessed December 3, 2019.; Hewlett, S. A. (2011). Elder care, child care, and the struggles of Chinese women. Harvard Business Review, April 8. Retrieved from https://hbr.org/2011/04/eldercare-childcare-andthe-st. Accessed December 3, 2019.

PAGE 46 The Researcher Journey Through a Gender Lens

More men

FIGURE 2.5

Gender ratio among thecohort of Chinese authors(authors active during theperiod 2014–2018).

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

All
Physics & Astronomy
Materials Science
Engineering
Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

More men

Gender ratio among
the cohort of Chinese
authors (authors active
during the period 2014–2018), grouped based on
the year of the author’s
first publication.

10

Parity between men and women

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

0

20

30

40

50

60

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Group B
Group CGroup D
Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

GROUP

10

More women

More men

FIGURE 2.6

20

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More women

YEAR OF FIRSTPUBLICATION

B

2004–2008C

2009–2013D

2014–2018

Research Footprint PAGE 47

FIGURE 2.7

2.7

Argentina
Average publication
Brazilcount during the period
Mexic0
Canada2014–2018 of menUSAand
EU28
women in the cohort
UK
Portugalof Chinese authors,
Spain
Francedisaggregated according
Italy
Netherlands
to publication history.
Germany

Averagepublication count

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

All
Group AAll

Group B
Group CGroup DAll

Physics &Astronomy

A
B
C

Denmark
Australia

D

Japan

KEY

GROUP

YEAR OF FIRSTPUBLICATION

All2018 or priorA

2003 or priorB

2004–2008C

2009–2013D

2014–2018

All

Materials
Science

C
D

All
A

Engineering

Women
Men

PAGE 48 The Researcher Journey Through a Gender Lens

A
B

B
C
D

Expert Interview

Charlina Vitcheva, MA, MS
Acting Director-General, Joint Research Centre (JRC)
European Commission (EC)How would you describe the current
state of gender diversity in research,compared with 5 years ago, and its
impact on research and/or researchers
globally and/or in your region inparticular?
The gender balance in research is improving in
the EU, but at a slow pace. Women in researchremain significantly underrepresented — around
one-third of all EU28 researchers are women.
The scientific quality and societal relevance of
produced knowledge, technologies and innovation
increases when they reflect the needs, behaviors
and attitudes of both women and men. Things are
moving in the right direction, but we need to do
more if we want to achieve a good gender balancein the near future.
On average, women today outnumber men atstudent and graduate levels and there is broad
gender balance at PhD level; however, theirdistribution in uneven across scientific fieldsof study, especially STEM fields, revealing apersistence of gender stereotypes. On a positivenote, the latest “She Figures” report indicates that
the EU is integrating the gender dimension in thecontent of scientific literature slightly better than
the world average.

Are there initiatives, policies, orinterventions that have emerged withinyour region and/or field in the last
3-5 years that you feel have impacted
progress and should be monitored toassess impact?
Gender equality and the integration of a gender
perspective in the preparation and evaluationof policies in academic research is a priority
for the EU. One action worth mentioning is the
Declaration on Women in Digital, signed earlier
this year by 26 EU Member States. Its purpose isto encourage women to play an active role in thedigital and technology sectors. One commitmentby the signatories is to monitor the evolution of

women’ engagement and participation in digitaljobs, careers and entrepreneurship through a
Women in Digital scoreboard. The demand forskills in artificial intelligence (AI) is expanding inseveral industries and AI specialists are becomingsome of the highest paid experts. If the gender
gap persists, it may widen the existing pay
disparities between men and women. Concrete
policy actions are thus necessary to support thefull participation and inclusion of girls and womenin the digital economy, while at the same time,
addressing stereotypes and social norms that leadto discrimination.

What value do data and an evidencebase offer as tools to policymakers andinstitutional leaders to address issues ofgender diversity and equity?
The European Commission (EC), under theguidance of President Ursula von der Leyen,
firmly believes that policy decisions should bebased on sound evidence. Data are essential tohelp quantify and qualify the issues of gender
diversity and equity, inform policies and design
programs. Data provides an objective measureof reality that informs policy choices and allows
us to monitor progress and evaluate the impactof those policies. The challenge that we often
face, including at the Joint Research Centre(JRC), is how to translate the data and scientificknowledge that we develop into informationthat inform policymakers. A good example is theSocial Scoreboard, a tool that accompanies theEuropean Pillar of Social Rights, which measuresand monitors equal opportunities and access to thelabor market.

Things are moving in the right
direction, but we need to do more
if we want to achieve a good genderbalance in the near future.

Expert Interview PAGE 49

What combination of interventions do
you think are necessary to accelerate
greater equity for women and men in
research?
It is essential to combine actions at theEuropean, national and institutional levels. With
its next Framework Programme, Horizon Europe,
the EC has reaffirmed its commitment to genderequality in research and innovation. The firstever Commissioner for Equality, Helena Dalli, hasestablished an inter-service and intersectional
Task Force on Equality. A new EC strategy forgender equality will be devised. In the researchsector, particular attention will be paid to genderbalance in evaluation panels and in bodies such as
expert and advisory groups. At the JRC, we havecommitted to a fully gender balanced staff and a
50% representation of women in all management
categories by 2030 at the latest.
I also think that gender equity in research should
not be limited to promoting greater women’s
participation. The unequal sharing of childcare
responsibilities within the family is one of themain reasons for shorter and more fragmented
careers in research among women. If we want toachieve true gender equity, we need to supportand empower both men and women at theorganizational level to achieve balance in theirpersonal and family life and work.

What information/insight fromthe report do you find particularlyinteresting and important forpolicymakers and institutional leaders
to consider in relation to your region ora specific subject area(s)?
I found the variation in gender distribution acrossthe disciplines particularly interesting, with fewer
women in the more technical and STEM-related
fields, from authors to grant receivers to inventors/
patent assignees. While initiatives are directed

PAGE 50 The Researcher Journey Through a Gender Lens

toward addressing this gap, its consistency acrossthe various facets of research makes it clear that weshould be doing more.

Trends identified from scientificpublications are confirmed for bothawarded grants and even more so whenanalyzing patents. What does this say
about a gender innovation gap?
To me, the gender innovation gap is linked to thelower presence of women in the more technicaldisciplines; it is evident that actions are needed toaddress this issue. Currently, women account for
approximately 30% of start-up entrepreneurs in
Europe; thus, female creativity and entrepreneurial
potential are a largely untapped resource. The
EC’s Entrepreneurship 2020 Action Plan supports
networking among female entrepreneurs, potential
female entrepreneurs and support organizations.
The JRC also supports the “EU Prize for Women
Innovators,” awarded to women who have received
EU research and innovation funding during theircareers, and then went on to establish a successfulcompany based on their innovative ideas.

What impact, if any, has the #MeToomovement had in the world of research?
The #MeToo movement has raised awareness ofworkplace sexual harassment, amplified previously
unheard voices, changed people’s perceptions ofwhat it means to be a sexual assault victim andhelped remove the stigma around experiencing
such misbehavior. The worldwide momentumof this movement has uncovered accusations ofsexual harassment and assault in fields of researchand science, with more women are willing toreport sexual harassment and its damaging effects
on their personal wellbeing and their scientificcareers. As stated in your report, there is extensive
literature on sexual harassment in academia and its
negative impacts on the academic climate and theresearchers’ job satisfaction.

The EC has begun to clarify the role of universities,
research organizations and support networks
in preventing sexual and gender harassment,
protecting victims and prosecuting perpetrators.
In my view, measures implemented at theorganization level should be evaluated to gain abetter understanding of their impact and informthe development and implementation of effective
policies and measures in academic environments
and research workplaces in Europe.

Thinking about the future of gender
diversity and equity in research globally,
where do you think we will be in 10
years’ time and what organizational
and/or cultural issues do you think will
influence change most significantly?

around gender issues is likely to suffer too. We
also need to do more to promote a better worklife balance for all researchers. Nevertheless,the current effort supporting women and girls’
empowerment is huge and the importance ofgender diversity is being recognized in various
areas, from the economy to the environment andclimate change.
Gender equality lies at the heart of the 2030
Agenda for Sustainable Development and thepledge to leave no one behind. With strong
support from the EC and President von der Leyen,the commitment to gender equality is strong inEurope. Initiatives to advance gender equality inresearch and innovation need to continue andexpand to strengthen the resilience and qualityof our democratic institutions and Europe’s
competitiveness.

I am positive — I think we will see an
improvement in the gender balance in research
globally. It will be necessary to address the
backlash against gender research and genderequality in some European countries. Where
academic freedoms are curtailed, critical thinking

Initiatives to advance gender equality
in research and innovation need tocontinue and expand to strengthen
the resilience and quality of ourdemocratic institutions and Europe’s
competitiveness.

Expert Interview PAGE 51

Research Footprint

Conclusion
Our analysis shows little difference in thecitation impact of women and men researchers,suggesting authors’ gender does not have abearing on the perceived quality of research
publications. However, differences observed in
the number of grant awards received may have
implications for the resources that are available
to women to carry out research. It may also haveconsequences in terms of women’s ability to
publish: if less funding means fewer projects, it
can be assumed that this would also negatively
impact the number of publications produced. A
similar logic may affect the number of patents
filed. Since research funding, publications andpatents are often used as measures of success of a
researcher’s career, it is possible that the observed
gender gap across these various types of research
output impact how women fare in the researchworld and inhibit the advancement of women tosenior roles. These gender gaps in research output
are likely to also affect the content of the research
portfolio.31 Ultimately, understanding the factorsthat contribute to these gender differences in
research output, for example, in researcher career
continuity and mobility as analyzed in Chapter 3
and in researcher networks described in Chapter
4, can provide insights into how we might addresssome of the observed inequalities.

31 Nielsen, M. W., Andersen, J. P., Schiebinger, L., & Schneider, J. W. (2017). One and a half million medical papers reveal a link between author gender and attention to gender and sex analysis. Nature Human
Behaviour, 1, 791-796. doi: 10.1038/s41562-017-0235-x

PAGE 52 The Researcher Journey Through a Gender Lens

Chapter 3

Publishing
Careers andMobility
Assessing author continuity and mobility

Key Findings• The ratio of women to men among authors in
the cohort declines over time (between the year of
authors’ first publication in 2009 up to 2018) in all
countries and regions except Portugal.
• In every country, the percentage of women who
continue to publish is lower than the percentage ofmen who continue to publish.
• In every country, the percentage of women who
publish internationally is lower than the percentage
of men who publish internationally.
• Those who publish internationally publish more andhave a higher FWCI than their counterparts who
do not publish internationally. However, in mostcountries and the EU28, among those who publish
internationally, men tend to publish more and havea slightly higher average FWCI than women.

Publishing Careers and Mobility PAGE 55

Publishing Careers and Mobility

Introduction
Chapter 1 revealed gender gaps related toparticipation in the research workforce andChapter 2 highlighted gender differences invarious types of outputs related to research, suchas publications, grant awards and patents. In thischapter, we turn our attention to the longevity of
research careers through an analysis of publishingrecords and researcher mobility. These twodimensions of a researcher’s career trajectory—
through time and space—offer important insights
into the reasons underlying the observed gender
gaps in representation among authors, grantawardees and inventors and the differencesin funding success, publications and patentapplications. Insights into the factors that contributeto gender gaps in representation and activity can beused to inform policies to redress gender inequities
in the world of research.
Several studies have revealed gender disparities in
researchers’ career trajectories.32 Men often havehigher starting salaries than women researchers
and are more likely than women to become
independent principal investigators.33 Women
researchers in academia experience a slower
pace of career advancement, spending moretime at the assistant professor level than men
researchers.34 Persistent implicit bias at the level of
institutions—in terms of hiring, provision of start-

up funds, mentoring support and promotion—may
contribute to the differences in career paths of men
and women researchers.35 Many women researchers
have non-linear career paths, for example, taking
time off for family reasons, which differentiallyaffects continuity and advancement in researchcompared to men.36
The ability to move to other countries to pursue
research opportunities, has a positive effect on
career advancement. The 2017 Elsevier Gender in
the Global Research Landscape report37 revealed
that men researchers are more mobile than
women, publishing more often outside theircountry of origin. The report further found thatpublications from mobile researchers are more
impactful than those from researchers who neverleft their country of origin. Differences in mobility
may thus contribute to gender disparities in
research career advancement.
In this chapter, we utilized bibliometric methods
to analyze how and where women and men
researchers publish over time,38 with the goal ofunderstanding whether gender differences can beobserved in the longevity of an author’s publishingcareer and how mobility impacts that aspect ofcareer progression.

32 Huang, J., Gates, A., Sinatra, R., & Barabasi, A. (2019). Historical comparison of gender inequality in scientific careers across countries and disciplines. arXiV preprint. Retrieved from: https://arxiv.org/
abs/1907.04103. Accessed December 2, 2019.; van den Besselaar, P., & Sandstrom, U. (2017). Vicious circles of gender bias, lower positions, and lower performance: gender differences in scholarly productivity andimpact. PLoS ONE, 12(8), e0183301. Retrieved from: https://doi.org/10.1371/journal.pone.0183301. Accessed December 2, 2019.
33 National Research Council. (2010). Gender differences at critical transitions in the careers of science, engineering, and mathematics faculty. Retrieved from: doi.org/10.17226/12062. Accessed October 23, 2019.;
van Dijk, D., Manor, O., Carey, L. B. (2012). Publication metrics and success on the academic job market. Current Biology, 24(11), R516-R517. doi:10.1016/j.cub.2014.04.039
34 Lerchenmueller, M. J., & Sorenson, O. (2018). The gender gap in early career transitions in the life sciences. Research Policy, 47(6), 1007-1017. Retrieved from: https://doi.org/10.1016/j.respol.2018.02.009. Accessed
December 2, 2019.
35 Charlesworth, T., & Banaji, M. (2019). Gender in science, technology, engineering, and mathematics. Journal of Neuroscience, 39(37), 7228-7243. doi: 10.1523/JNEUROSCI.0475-18.2019; Mallapaty, S. (2018). Q&A
Mary Frank Fox: Time to ditch the leaky pipeline model. Nature Index, May 25, 1–10. https://www.natureindex.com/news-blog/mary-frank-fox-time-to-ditch-the-leaky-pipeline-model; Hofstra, B., Galvez, S., He,
B., Kulkarni, V., & McFarland, D. (2019). Diversity breeds innovation with discounted impact and recognition. arXiv preprint. Retrieved from: https://arxiv.org/abs/1909.02063. Accessed December 2, 2019.; Eaton,
A., Saunders, J., Jacobson, R., & West, K. (2019). How gender and race stereotypes impact the advancement of scholars in STEM: professors’ biased evaluations of physics and biology post-doctoral candidates.
Sex Roles. doi: 10.1007/s11199-019-01052-w
36 Cech, E., & Blair-Loy, M. (2019). The changing career trajectories of new parents in STEM. Proceedings of the National Academy of Sciences, 116(10), 4182-4187. doi: 10.1073/pnas.1810862116
37 Elsevier. (2017). Gender in the Global Research Landscape. https://www.elsevier.com/research-intelligence/campaigns/gender-17. Accessed October 23, 2019.
38 Robinson-Garcia, N., Sugimoto, C. R., Murray, D., Yegros-Yegros, A., Larivière, V., & Costas, R. (2019). The many faces of mobility: using bibliometric data to measure the movement of scientists. Journal of
Informetrics, 13(1), 50–63. doi: 10.1016/J.JOI.2018.11.002

PAGE 56 The Researcher Journey Through a Gender Lens

Publishing Careers and Mobility

Assessing the Continuityof Authors Over TimeTo examine gender-related differences in how
long authors continue to publish, we assessed
the publishing records of a cohort of individuals
whose first paper appeared in Scopus in 2009.
Authors in this cohort were then assigned tocountries and subject areas based on their
publications during the period 2009­-2014 (seeadditional details in Appendix A). Once we defined
the cohort of individuals based on authors’ firstyear of publication, we determined the year ofeach author’s last publication in Scopus (up to2018). Authors in the cohort were included in theauthor count for each year until the year of theirlast publication. For example, an author who firstpublished in 2009 and last published in 2015 was
not included in the author count from 2016 to 2018.

Taking this approach, we observed that in every
country, there was a decline in the total number ofpublishing authors over time. The biggest drop wasobserved after the first year. Among the 15 countries
that were assessed and the EU28, only 46-60%
of authors who first published in 2009 publishedagain by 2018. These authors, who published only
once in 2009 and then did not publish again, may
have been researchers who left research or researchsupport staff whose contribution to a research
project was acknowledged through authorship.
We assumed that this group of individuals was
likely heterogeneous across countries dependingon local authorship practices, the inclusion ofundergraduates in research, the prevalence of
support research staff in the research ecosystemand the minimum publication requirements set for
graduate students. Thus, we focused our analysis
on authors who published at least twice during theperiod 2009–2018.

Publishing Careers and Mobility PAGE 57

If women and men continued to contribute as
authors for the same length of time after theirfirst publication, the gender ratio would remain
stable over time. In most countries analyzed, we
found that the number of women who continued
to publish declined more rapidly over time
relative to the number of men who continued to
publish (Figure 3.1). In the EU28 and in 14 of the
15 countries included in the analysis, the ratio of
women to men who continued to publish declined
at a rate ranging from -0.004/year (in Japan) to-0.016/year (in Argentina). In real terms, thiscorresponded to a slightly higher rate of loss inwomen authors compared to men authors overtime (supplemental data, Table B.6). For example,
in Brazil, there were 7,181 women authors in thecohort in 2010, which declined by 623 women peryear (-8.7% per year); by comparison, there were
9,185 men authors in the cohort in 2010, which
declined by 749 men per year (-8.2% per year).
Therefore, the decline in the ratio of women to men
was due to a 0.5% greater decline in the numberof women than men authors over the study period.
Portugal stands apart in that the ratio of women
to men increased slightly over the study period, at
a rate of 0.003/year. Interestingly, in the previous
Elsevier report, Portugal was found to have oneof the highest levels of gender parity in terms ofoverall research participation.

PAGE 58 The Researcher Journey Through a Gender Lens

The more rapid decline in the number of womenamong authors compared to men is illustrated
in Figure 3.2. By 2018, in all countries with adecline in ratio of women to men, we observeda small gap in the percentage of women who
continued to publish compared to men. A chisquare test of independence comparing thedifference in proportions confirmed that thisdifference was significant (i.e., p < 0.05) for all
countries except the Netherlands, Mexico andPortugal (supplemental data, Table B.6). Similar
trends in the decline of women authors wereobserved for authors who first published in 1999
(supplemental data, Figure B.11). This small but
significant difference in the proportion of womencompared to men who continued to publish nine
years after their first publication could be related
to a variety of factors. In Elsevier’s 2019 survey ofresearchers, half of respondents said that they havecontemplated changing careers, primarily because
of inadequate pay or to pursue an exciting career
opportunity. Almost a quarter of women said
that they have considered leaving their career in
research for reasons other than to pursue a careeroutside of research. Women, more so than men,cited reasons such as family commitments, thata research career is too demanding or that theyexperienced discrimination or harassment at work
(Appendix C, Figure C.5).

3.1

Gender ratio among Argentina
authors whose first Brazil
Mexic0
Canadapublication was in 2009USA
and who published again
EU28
UK
at least once in any year
PortugalSpain
up to 2018.
France2010
More women

FIGURE 3.1

BrazilJapan

MexicoCanadaUSA

Australia

143 70125 80111 90100
90 11180 125

Portugal

50 20040 250France30 333Italy

20 50010 1000

Men per 100 women

0 ∞Women per 100 men

More men

Spain

Japan

2018

167 6070 143Australia

2017

500 2060 167

Denmark

2016

∞ 0

UK

Germany

2015

1000 10EU28

Netherlands

2014

200 50Parity between men and women

Denmark2013

250 40Netherlands

Argentina

2012

333 30Italy
Germany

2011

FIGURE 3.1 TAKEAWAY:

The ratio of women to men among authors in the cohort declines over time
(between the year of authors’ first publication in 2009 up to 2018) in all
countries and regions except Portugal.

Publishing Careers and Mobility PAGE 59

3.2

Percent of women andArgentina
men in each country Brazil
Mexic0relative to the numberCanada
USAof authors in the cohort
EU28
UK
in 2010. The cohort is Portugal
comprised of authors Spain
Francewhose first publicationItaly
was
Netherlands
Germany
in 2009 and subsequently
Denmark
published at least one AustraliaJapanmore publication during
the period.

2010

2011

2012

2013

2014

2015

2016

2017

2018

100
90
80
70
60
Women

FIGURE 3.2

50
40
30
20
10
0
100
90
80
70

Brazil60

Mexico

50

USA
EU28
UK
Portugal
Spain
France

40
30
20
10
0
Percent

CanadaMen

Argentina

Italy
Netherlands
Germany
Denmark
Australia
Japan

PAGE 60 The Researcher Journey Through a Gender Lens

FIGURE 3.2 TAKEAWAY:

In every country, the percentage of women who continue to publish is lower
than the percentage of men who continue to publish.

Publishing Careers and Mobility

Gender and Researcher
Mobility Trends
Researchers who work in other countries
often reap benefits as a result of their time
abroad. Conducting research in another country
can broaden a researcher’s exposure to newtechniques, strengthen their network and inspire
new ideas. We observed that among authors,
those who published outside their country oforigin at least once had a lower rate of attrition(supplemental data Figure B.12). Among those still
publishing in 2014–2018, authors who publishedoutside their country of origin at least once
published more on average and had a higher FWCI
than those who never published outside theircountry of origin. Given the benefits of gaining
international research experience, we assessed
whether there exist gender-based differences inauthor mobility, measured on the basis of whether
authors have published with an affiliation outside
their country of origin (i.e., internationally).

HOW WE ASSESSED MOBILITY

The country of origin of each author wasinferred based on the country of affiliation
listed in their first publication. The authors
were then assigned to one of two groups
based on their publication history: authors
who have published internationally (i.e.,
outside their country of origin) and authors
who have never published outside theircountry of origin. To control for authors’level of experience, we limited the cohort
to authors who first published during afive-year window (2009–2013 or 1999–2003).
Additionally, we excluded authors who
published only once in their career because
this group of authors was assumed to beheterogeneous (representing undergraduate
researchers, research support staff andresearchers who left academic research) andvary based on local authorship practices.
Detailed methods on the mobility analyses
are provided in Appendix A.

Publishing Careers and Mobility PAGE 61

Those who publish internationally publish more andhave a higher FWCI than their counterparts who
do not publish internationally. However, in mostcountries and the EU28, among those who publish
internationally, men tend to publish more and havea slightly higher average FWCI than women.
Among authors in both cohorts, we observed thatmen were more likely to publish internationallythan women (Figure 3.3). Among authors who firstpublished in the period 2009-2013 and publishedinternationally at least once, there was a persistent
gap in the percentage of men compared to women
who published internationally. This gap ranged
from 1.3 percentage points in Japan (6.2% of men
published outside Japan compared with 4.9% of
women) to 7.7 percentage points in France (25.3%of men published outside France compared with
17.6% of women). Assessing trends over a longer
period of time among those authors who firstpublished in the period 1999-2003, revealed awider gap between the genders, ranging from a
3.4 percentage point difference in Japan (11.7% of
men published outside Japan compared with 8.3%
of women) to an 11.1 percentage point differencein Denmark (33.5% of men published outside
Denmark compared with 22.4% of women).
Our findings are consistent with an Elsevier
survey of researchers conducted that showedthat more men than women agreed with thestatement “I am considering moving to anothercountry to further my career in research.” Thedifference was greatest in Eastern Europe andLatin America (supplemental Figure C.6). For both
men and women, family commitments and lackof invitations from international institutions were
inhibitors to relocation.
To assess whether the benefits of publishinginternationally were equal among men andwomen, we analyzed metrics related to each cohort
based on author status and publication record
during the period 2014-2018. We observed a higher
rate of author continuity among both women andmen who published internationally compared tothose who published solely in their country oforigin. However, the rate of attrition was higher
among women than men in the long term (Figure3.4). Among those who published for the first timein 2009–2013 and published internationally atsome point, 90–95% of women and men publishedagain in 2014–2018 in the countries studied and

PAGE 62 The Researcher Journey Through a Gender Lens

little difference was observed between men andwomen. However, among those who first publishedin 1999-2003 and published internationally, thepercentage of women who published again in
2014-2018 ranged from 60.6% (in Germany) to
81.5% (in Portugal) while among men, the range
was higher, from 69.7% (in Germany) to 84.4% (inArgentina). This indicates that although the attrition
rate is lower among those who have publishedinternationally, this does not compensate for thehigher rate of attrition among women compared tomen over an extended period of time.
Comparing the 2014-2018 publications among
women and men from each cohort, we observedthat women who published internationallypublished more and had a higher FWCI on averagethan those who only published in their country oforigin (supplemental data Figure B.13). However,the difference between men and women in bothaverage publication count and FWCI was greater
among those who published internationally thanamong those who never published internationally(Figure 3.5). Among the 2009-2013 cohort, men who
never published internationally during their careers
had between 1.1 times more (in the Netherlands)
to 1.3 times more (in Germany) publications than
women in the same category. Among those who
did publish internationally, the values were higher,
ranging from 1.2 times more (in Argentina) to 1.7
times more (in Denmark) publications by men than
women. Similarly, men’s average FWCI ranged
from 0.87 times that of women (in Mexico) to 1.03
times that of women (in Italy) among those who
never published internationally. Among those who
did publish internationally, the average FWCI ofmen ranged from 0.95 times that of women (inFrance) to 1.16 times that of women (in Japan). Thissuggests that although publishing internationallyimparts an advantage (in terms of average
publication count and FWCI), the publication
metrics gap between men and women is wider
among those who publish internationally thanthose who do not. Further analyses are needed
to assess whether subject area differences in
representation or authorship position account forthe observed gender gaps in authors who publish
internationally.

3.3
FIGURE 3.3

3.3

Percent of authorsArgentina
whoBrazilfirst published in Mexic0
1999–
Canada2003 (top) or 2009–2013
USA
EU28(bottom panel) who
UK
Portugalpublished internationallySpain(i.e., outside theirFrance
country
Italy
Netherlandsof origin) at least once.
Germany

Percent

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

First publicationin 1999–2013

First publicationin 2009–2013

Denmark
Australia
Japan

KEY

Percent

Women
Men
Argentina

Spain

BrazilFranceMexicoItaly

CanadaNetherlands

USA

Germany

EU28

Denmark

UK
Portugal

FIGURE 3.4

FIGURE 3.3 TAKEAWAY:

In every country, the percentage of women who publish internationally is lower thanthe percentage of men who publish internationally.

3.4
Australia
Japan

3.4

Percent of authorsArgentina
whoBrazilpublished internationally
Mexic0
Canada(i.e., outside theirUSA
country of origin)EU28
andUK
who published at Portugal
least
Spain
Franceonce in 2014–2018.
Data
Italy
Netherlands
shown for those who
first
Germany
published in 1999–2003
Denmark
Australia(top) and 2009–2013
Japan(bottom).

Percent

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

First publicationin 1999–2013

First publicationin 2009–2013

Percent

KEY
Women
Men
Argentina

Spain

BrazilFranceMexicoItaly

CanadaNetherlands

USA

Germany

EU28

Denmark

UK

Australia

Portugal

Japan

Publishing Careers and Mobility PAGE 63

FIGURE 3.5

Men publish more

3.5

Ratio of average
Argentina
publication count (top) Brazil
Mexic0
Canadaand average FWCI
USA
(bottom) of men
EU28
UK
compared to women
Portugalauthors, among those Spain
Francewho first published in Italy
Netherlands
Germany
2009-2013, disaggregatedDenmark
Australia
according to author
Japancountry of origin andwhether the author
has ever publishedinternationally.

Women to men 0.50
Men to women

2.0

Parity between men and women

0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91
1.9

1.8

1.7

1.6

1.5

1.4

1.3

Brazil

1.1

1.0

1.2

Women publish more

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50

Sedentary

International
experience

Women to men 0.50
Men to women

2.0

0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91
1.9

1.8

1.7

1.6

1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

1.3

1.4

1.5

1.6

Women to men 0.50
Men to women

2.0

1.8

1.8

1.9

2.0

Women publish more

Parity between men and women

0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91
1.9

1.7

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50

Men publish more

Men are cited more

Argentina

1.2

1.1

1.7

1.6

1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

Women are cited more

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50

MexicoCanadaUSA

Sedentary

EU28
UK
Portugal
Spain
FranceInternational
experience

Italy
Netherlands
Germany
Denmark
Australia
Japan

PAGE 64 The Researcher Journey Through a Gender Lens

Women to men 0.50
Men to women

2.0

0.53 0.56 0.59 0.63 0.67 0.71 0.77 0.83 0.91
1.9

1.8

1.7

Men are cited more

1.6

1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50
Women are cited more

Expert Interview

Miyoko O. Watanabe, PhD
Deputy Executive Director and Director, Office for Diversity and Inclusion
Japan Science and Technology Agency (JST)How would you describe the current
state of gender diversity in research,compared with 5 years ago, and its
impact on research and/or researchers
globally and/or in your region inparticular?
In Japan, the ratio of women to men researchers
is continuously increasing, but it is happening
very slowly. The government set a target toincrease the share of women researchers to
30% by 2020, but by 2019 we had only achieved
16.6%. I believe the pace of change has been soslow because decisions are made by consensus
after extensive discussion between multiple
stakeholders, rather than by a few decisionmakers. While there are advantages to consensusbased decision making, it has slowed theprogress towards achieving gender equality inJapan. I should also say that Japanese people arealso perfectionists: they may avoid addressing
something that they cannot perfect. Perhaps it istime for us to focus on issues that really require
attention, even if we cannot achieve perfection.

Are there initiatives, policies, orinterventions that have emerged withinyour region and/or field in the last
3-5 years that you feel have impacted
progress and should be monitored toassess impact?
We hosted the Gender Summit in Tokyo in 2017,and it turned out to be a good opportunity forJapan to think about gender equality and initiatechange. At the Summit, we presented encouraging
data from the Development Bank of Japan showingthat the economic value of patents from gendermixed teams was higher than that of patents frommale-only teams. These data were re-analyzed
last year, and confirmed that the economic valueof patents from gender-mixed teams was 54%
higher. Data like this—that describes the economic
impact of women’s contributions to research—isparticularly impressive and effective at changing
minds and policy in Japan.

By comparison, data on the ratio of women tomen researchers or how slowly it is changing isalmost too simple because it does not give us
answers about why or how to change it. Japanese
researchers want to know about how we got
here, not just the result. Our objective in genderequality is not really to achieve a 50:50 ratio, but foreveryone to receive equal opportunity and create asociety that is inclusive of all kinds of people.

What value do data and an evidencebase offer as tools to policymakers andinstitutional leaders to address issues ofgender diversity and equality?
In the past, we did not have a lot of data.
Decisions were made based on people’s
experiences. Today, data gives us the opportunity
to change our decision-making process fromsomething driven by experience and opinion tosomething that is truly evidence-based. There isa generational component to making this shift—
younger people are much more data-literate andare able to use and analyze data more effectively
than older people who tend to make decisions
based on their experience.

What information or insight fromthe report do you find particularlyinteresting and important forpolicymakers and institutional leaders
to consider in relation to your region or
specific subject areas?
The qualitative analysis is quite interesting.
For example, most researchers said that there
are more women in research now compared
to 10 years ago, which is consistent with mythoughts. I am slightly anxious, however, about theconsequences for young men and boys entering
careers in research. Among young researchers
right now, it appears easier for young womento get permanent jobs, because many people,
managers, and societies want to see an increase in
women’s participation in research. The emphasis
really needs to be on inclusion and opportunity foreveryone, regardless of gender.

Expert Interview PAGE 65

Gender equality is not an isolated
problem—it is related to age,
race, ability, culture, sexuality, andgeography, among other factors.

My opinion is framed by the fact that Japan willsoon experience a drastic depopulation, and manyother countries will follow. Considering China’s
massive population, depopulation in China will
have a global effect. In a growing society, efficiency
is very important, and the individual is less valued.
However, in a shrinking society, there is opportunity
for everyone to have a place and contribute.

In the report there are trends identified
from scientific publications, which areconfirmed for both awarded grants andeven more so when analyzing patents.
What does this say about the genderinnovation gap?
I think there is a huge innovation gap in Japan.
Traditionally, men were considered to be theinnovators, the inventors. But there are many
new ventures in Japan now, and you can really
see the difference between those founded bymen and women. I get the impression that men
founders are interested in industries separated
from our daily life, whereas women founders are
more interested in new industries connected toour daily lives. Businesses founded by men often
achieve a net positive value on a shorter timescaleand raise more capital, but the companies have ahigher failure rate. On the other hand, businesses
founded women might take longer to achieve a net
positive value, but once they do, they are successful
for a longer time. Both types of businesses areimportant, so we should continue to promote both
men and women.
With regard to funding, I recently analyzed dataon venture capital in the US for the World Science
Forum. Over 90% of decision-makers at top venture
capital firms are men. If you look at how venture
capital firms make investments, 85% of theirinvestments go to start-ups founded by men, while
13% go to mixed-gender teams, and only 2% go towomen founders. This is consistent with the report’s
findings that men select and support other men.

PAGE 66 The Researcher Journey Through a Gender Lens

I am also on the World Science Forum organizing
committee, which decides on candidates forplenary speakers. The committee is 64% female.
The steering committee, which decides on theactual speakers, is 35% female. The final ratioof plenary speakers at this year’s World Science
Forum was 53% female. So, from this example, it
is clear that when women and men work together,
they select both women and men and together
achieve gender balance in the group.

Thinking about the future of gender
diversity and equity in research globally,
where do you think we’ll be in 10
years’ time and what organizationaland or cultural issues do you think will
influence change most significantly?
I always say that gender equality is not an isolated
problem—it is related to age, race, ability, culture,sexuality, and geography, among other factors. If
we only talk about gender equality, we lose sight ofthese connections. We should be promoting genderequality in the context of these other factors, with afocus on diversity, not just gender.
In addition, I feel that many senior men are simply
unaware of women’s talent in Japan. This year
we launched the 1st Brilliant Female ResearchersAward (Jun Ashida Award) for excellent women
researchers and institutions promoting women inscience. We always wondered why we didn’t have
many women researchers applying for funding, but
for this award, we had over 100 applicants. Many ofus were unaware of these talented women prior tolaunching this award. We need to continue creating
platforms to support and promote women.

Publishing Careers and Mobility

Conclusion
In this chapter, we observed that men wereslightly more likely to continue to contributeto research as authors than women, based on acohort analysis of researchers’ publication records
over time. Indeed, our survey revealed that womenleaving research careers tend to mention family
commitments and harassment or discrimination
more frequently than men. Of these two reasonsfor leaving research, the first may be rooted
in personal choice as well as the cultural andsocietal expectations placed on women. The
second reason may be addressed through thedevelopment and implementation of policies
and procedures that ensure safe and respectful
workplaces at research institutions.

Our analyses also revealed that men publish moreinternationally than women. However, while those
who publish internationally tend to have a higher
number of publications and higher citation impact,a gender gap in these two indicators persists withwomen trailing men on both counts. It seems
that women researchers are not able to benefit
equally from international mobility, in terms ofparticipation as well as outcomes. This reinforces
the hypothesis from the 2017 Elsevier report that
there exists a “glass fence” that limits international
mobility of women researchers, and thus their
future research career success. There are several
factors that may impact the international mobilityof researchers, such as one’s collaboration network,
which is the focus of the next chapter.

Chapter 4

Collaboration
Networks
Evaluating gender differencesin collaboration activity

Key Findings• Across many subject areas and countries, men
tend to have more co-authors than women andthis difference is wider for authors with a longer
publication history.
• Women and men are more similar in the way
they are connected to their potential collaborative
space (second-order collaborators) through theirdirect collaborators.
• Women and men researchers are similar withrespect to their share of international collaborators,
except for the EU28, where men have a slightly
higher tendency to establish international
collaborations than women.
• On average, authors tend to preferentiallycollaborate with authors of the same gender acrossthe subject areas and regions studied.

Collaboration Networks PAGE 69

Collaboration Networks

Introduction
In this report, we used a network analysis
approach to study whether gender impacts
authors’ collaboration relationships. Network
analysis provides a unique perspective that reveals
the complex nature of relationship structure among
researchers and the characteristics of authors’collaborative networks. It is through complex
interactions between individuals and institutions
that processes of knowledge diffusion, innovation40
and individual career progression take place.
Assessing collaboration through network analysis
allows us to consider complex interactions
between an author’s characteristics and thecharacteristics of their co-authors. For example,
an author may have a relatively high number ofcollaborators who have co-authors who are notwell-connected or experienced. Conversely, anauthor may collaborate with a relatively low numberof exceptionally well-connected and/or experienced
co-authors. In this context, network analysis canevaluate whether opportunities to connect to otherauthors in the research community are greater inthe latter case than the former, despite the former
having a higher number of co-authors.41 A network
analysis approach also allows us to examine direct

and indirect co-authorship ties of an author(i.e., the focal author) to assess how the network
positioning and productivity of co-authors (i.e.,
direct collaborators of the focal author), and coauthors’ co-authors (i.e., second-order collaboratorsof the focal author), relate to individual research
output and scientific trajectory.42
Scientific collaboration is impacted by gender, as
well as other social identities. Because gender isa factor that has been shown to influence social
interactions, gender may also determine exclusion
or subordination within scientific institutions.43
Therefore, it is relevant to examine how men andwomen are positioned in collaboration networks,
as their network characteristics may be shaped bygender differences and form the basis for futureand downstream scientific activity.
In this chapter, we add to a growing literature on
men’s and women’s positioning in the structureof scientific collaboration with a study of coauthorship network using a sample of authors
in 16 networks defined by the focal authors’geographic region and subject area (referred toas region-subject pairs) where the region was

40 Whittington, K. B., Owen-Smith, J., & Powell, W. W. (2009). Networks, propinquity, and innovation in knowledge-intensive industries. Administrative Science Quarterly, 54(1), 90-122. doi: 10.2189/
asqu.2009.54.1.90; Barabási, A., Jeong, H., Néda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and its Applications,311(3-4), 590-614. doi: 10.1016/S0378-4371(02)00736-7
41 Madlock-Brown, C., & Eichmann, D. (2016). The scientometrics of successful women in science. In Advances in Social Networks Analysis and Mining (ASONAM), 2016 IEEE/ACM International Conference on
Advances in Social Networks Analysis and Mining (pp. 654–660). IEEE. Retrieved from: https://doi.org/10.1109/ASONAM.2016.7752307. Accessed December 5, 2019.
42 Bordons, M., Aparicio, J., González-Albo, B., & Díaz-Faes, A. (2015). The relationship between the research performance of scientists and their position in co-authorship networks in three fields. Journal of
Informetrics, 9(1), 135-144. doi: 10.1016/j.joi.2014.12.001; Dehdarirad, T., & Nasini, S. (2017). Research impact in co-authorship networks: a two-mode analysis. Journal of Informetrics, 11(2), 371-388. doi: 10.1016/j.
joi.2017.02.002; Ebadi, A., & Schiffauerova, A. (2015). How to become an important player in scientific collaboration networks? Journal of Informetrics, 9(4), 809-825. doi: 10.1016/j.joi.2015.08.002; Warner, E. T.,
Carapinha, R., Weber, G. M., Hill, E. V., & Reede, J. Y. (2016). Faculty promotion and attrition: The importance of coauthor network reach at an academic medical center. Journal of General Internal Medicine, 31(1),60-67. doi:10.1007/s11606-015-3463-7.
43 Whittington, K. B. (2018). A tie is a tie? Gender and network positioning in life science inventor collaboration. Research Policy, 47(2), 511-526. doi:10.1016/j.respol.2017.12.006; Abramo, G., D’Angelo, C. A. &Murgia, G. (2013). Gender differences in research collaboration. Journal of Informetrics, 7(4), 811-822. doi: 10.1016/j.joi.2013.07.002; Beaudry, C. & Larivière, V. (2016). Which gender gap? Factors affecting
researchers’ scientific impact in science and medicine. Research Policy, 45(9), 1790-1817. doi: 10.1016/j.respol.2016.05.009; van Emmerik, I. H. (2006). Gender differences in the creation of different types ofsocial capital: A multilevel study. Social Networks, 28(1), 24-37. doi: 10.1016/j.socnet.2005.04.002; Bozeman, B., & Gaughan, M. (2011). How do men and women differ in research collaborations? an analysis of
the collaborative motives and strategies of academic researchers. Research Policy, 40(10), 1393-1402. doi: 10.1016/j.respol.2011.07.002; Warner, E. T., Carapinha, R., Weber, G. M., Hill, E. V., & Reede, J. Y. (2015).
Faculty promotion and attrition: the importance of coauthor network reach at an academic medical center. Journal of General Internal Medicine, 31(1), 15–17. doi: 10.1007/s11606-015-3463-7; Ghiasi, G., Larivière,
V., Sugimoto, C. R., Larivi, V., & Sugimoto, C. R. (2015). On the compliance of women engineers with a gendered scientific system. PLoS ONE, December(12), 1–19. doi: 10.1371/journal.pone.0145931

PAGE 70 The Researcher Journey Through a Gender Lens

Brazil, Japan, USA or the EU28 and the subject
area was biochemistry, business & economics,
engineering or medicine (see Appendix A, sections“Author country and subject area assignation”
and “Author mobility”). Brazil, Japan, USA andthe EU28 were selected for our analyses because
they were expected to reflect different research
cultures and have different ratios of women tomen among authors. 44 Biochemistry, business &economics, engineering and medicine were chosen
as representative subject areas from each of thefour broad subject clusters: life sciences, social
sciences, physical sciences and health sciences,respectively, with different ratios of women tomen among authors. 45
We measured authors’ network centrality (i.e.,the count of co-authors) and the average network
centrality of their direct collaborators, as depicted
in Figure 4.1. We paid particular attention to
4.1
the attributes of authors’ immediate ties, to thecharacteristics of these ties, to tendencies towards
gender homophily (proportion of same-gender ties)
and the nature of men’s and women’s internationalreach (proportion of collaborators affiliated withdifferent countries). These analyses are a starting
point from which we can consider how gendershapes collaborative activity in research.
Our analyses focused on a set of focal authors
who published during the year 2013 and were“active authors.” A full description of how focal
authors were defined can be found in Appendix A,
section “Author collaboration network analysis.”
We built collaborative network profiles for theseauthors based on their co-authorships fromthe period 2009-2013 and built an author-level
collaboration network in which the “nodes” in the
network represent authors and the connections
between them (the “links”) represent co-authorship
relationships (i.e., authorship of one or more
publications by two authors during the period).

FIGURE 4.1

A simple ideal collaboration
network. The focal author (black
circle) is tied to two direct coauthors (blue and red circles),which are in turn connected to
five co-authors (gray circles).
This results in a direct network centralityof the focal author equal to 2 and an
average network centrality of their direct
collaborators equal to 5. Each individual
direct collaborator can be assigned abinary attribute according to gender andregion (same or different from the focal
author’s), represented here as different
node colors (blue and red), to compute
gender composition and internationalityof the focal author’s direct co-authors.

44 Elsevier. (2017). Gender in the Global Research Landscape. Retrieved from: www.elsevier.com/research-intelligence/campaigns/gender-17. Accessed October 23, 2019.
45 Ibid.

Collaboration Networks PAGE 71

Collaboration Networks

Network Centralityof Focal Authors
An author collaboration network can be firstdescribed by the count of direct collaborations
established over a certain period of time, referred
to in our analyses as “network centrality.” To
understand if gender contributes to the formationof research collaborations, we assessed the average
network centrality46 for men and women authors in
networks defined by 16 region-subject pairs.
Figure 4.2 depicts the average network centralityof men and women focal authors as a function of
their first year of publication in 16 region-subject
pairs. The absolute value of average network
centrality within each gender group was normalized
to the average network centrality of observations
within each group of authors of the same region,
subject area and year of first publication to isolate

the difference between the two gender groups. In
other words, any differences observed across men
and women within a given region, subject area andyear of first publication would be due to gender.
Figure 4.2 shows that there were similar trends
across regions, with the least difference between
men and women among the younger cohorts(based on year of first publication) and thedifference increased with longer author publication
histories. The difference in network centrality bygender was greatest in medicine. We observed
more variable trends in engineering and business& economics in Japan and Brazil, which may be dueto the small number of observations forthese cohorts. 47

Network centrality
We measure network centrality as the number of direct collaborators, i.e., the number of uniqueauthors with whom an author has co-authored papers during a period of time. In network
science, this measure is called “degree centrality.” See also Appendix A for details on modeling andcomputation of network centrality.

46 For this analysis, we counted the number of each author’s direct co-authors during the period 2009–2013, excluding possible collaborations prior to 2009 or collaborations that were not captured as coauthorship on a published paper.
47 For completeness, we included focal author cohorts from Japan and Brazil in analyses of engineering and business & economics and more senior cohorts from EU28 in business & economics, as these cohorts
included a small number of observations. The aggregate statistics for these groups cannot be considered reliable as they can generate fluctuating trends. Therefore, we intentionally avoided interpreting theresults for these cohorts.

PAGE 72 The Researcher Journey Through a Gender Lens

FIGURE 4.2

4.2

Group
Normalized numberofA
1989-1993
direct collaboratorsGroup B
1994-1998(x-axis) of focal authors,
Group C
1999-2003
grouped based on year
Group D
2004-2008of their first publication
Group E
2009-2013(y-axis), by region andsubject area.

Values were normalized byaverage values of observations
by region, subject area andbinned focal authors’ year offirst publication. Average values
corresponding to less than 10
observations were excluded fromthe analysis.

Average network centrality(Normalised number of 0.5
direct collaborators)

Brazil

0.75

Japan

1.0

1.25

1.5 0.5

0.75

1.0

1.25

1.5 0.5

0.75

USA

1.0

1.25

1.5 0.5

0.75

1.0

1.25

1.5 0.5

0.75

EU28

1.0

1.25

1.5 0.5

0.75

1.0

1.25

1.5 0.5

0.75

1.0

1.25

1.5

1.0

1.25

1.5

Group AGroup B

Medicine

Group CGroup DGroup EA
B

Biochemistry

C
D
E
A
B

Engineering

C
D
E
A
B

GROUP

YEAR OF FIRSTPUBLICATION

A

1989–1993B

1994–1998

C

1999–2003D

2004–2008E

2009–2013

Business &Economics

C
D
E

0.5

0.75

Brazil

Japan

USA

EU28

FIGURE 4.2 TAKEAWAY:
Women
Men

Across several regions and subject areas, men tend to have more co-authors than women andthis difference widens for authors with a longer publication history.

Collaboration Networks PAGE 73

Collaboration Networks

Characteristics
of Collaboration Ties
To provide insight on the gender differencesin collaboration beyond the average number ofco-authors, we considered several characteristics
of men and women authors’ collaborators. We
studied:• how well-connected the direct collaborators ofmen and women authors are (on average),• the proportion of men and women authors’collaborators who are the same gender(gender homophily) and• the proportion of men and women authors’collaborators who were “international”
collaborators (i.e., affiliated with a different
country).
Responses to Elsevier’s 2019 survey of active
researchers provided insights into the qualityof their social networks. Active researchers(self-identified as spending at least 20% of theiracademic/work activity conducting research on an
ongoing basis) were asked if they know (i.e., if they
are able to remember the name of the person/
job holder and easily start a conversation when
encountering them) people who hold certain job
positions of varying levels of prestige within theirfields. Women reported having more close ties withpeople in positions of moderate prestige, whereas
men reported knowing people considered to be

PAGE 74 The Researcher Journey Through a Gender Lens

in positions of high prestige. These influential
connections, as a measure of research network
quality, could allow for greater career mobility
and a distinct advantage in career progression
opportunities (Appendix C, Figure C.7).
The survey also found that, when defining
seniority by years in research, similar percentagesof men (59%) and women (57%) in later stagesof their research careers (i.e., actively involved
in research for 10 or more years) reported having
at least one high-prestige connection. Among
early-career researchers (i.e., actively involved inresearch for less than 10 years), significantly fewer
women (38%) reported having at least one highprestige connection compared to men (49%). These
differences in social network quality may contributeto the observation that fewer women gain seniorleadership roles (Appendix C, Figure C.8).
In the 2019 Elsevier survey, significantly more
women (70%) than men (64%) agreed that it iseasy to collaborate with colleagues in their fieldof research. This suggests that women may bebetter at creating close-tie connections, or that men
may be actively reaching out to collaborate more
often, but these attempts do not always result in acollaboration (Appendix C, Figure C.9).

The network centrality of direct collaborators
Beyond the number of direct collaborators, anauthor’s collaboration network properties can beassessed by looking at potential collaborations,
qualifying the strength of each direct connection
based on how many potential other connections
a direct collaborator would unlock for the focal
author. We assessed how well-connected a focal
author’s direct collaborators are by calculating thenumber of collaborators of the direct collaborator.
These collaborators of the direct collaborator arereferred to as second-order collaborators (in Figure
4.1, second-order collaborators are depicted as graydots, see also the definitions in Appendix A, section“Author collaboration network analysis”). We thencalculated the average number of second-ordercollaborators of each focal author. If a focal author’s
average number of second-order collaborators ishigh, this indicates that the focal author has highvalue direct collaborators. Therefore, the average
number of second-order collaborators may beconsidered as a measure of the network “reach,”to the available social capital held by the direct
collaborators of a focal author. The implicationis that the more co-authors an author’s direct
collaborators have, the wider the current and/or
future collaborative space is for that author.
Figure 4.3 depicts the average number of
second-order collaborators of men and women
focal authors as a function of their first yearof publication, in 16 region-subject pairs. We
normalized the average number of second-ordercollaborators within each gender group to theaverage number of second-order collaborators
within each group of authors of the same region,
subject area and year of first publication to examine

the difference between the two gender groups.
Thus, any differences observed across men andwomen within a given region, subject area and yearof first publication would be due to gender.
As Figure 4.3 shows, we found that collaboratorsof men and women focal authors acrosspublication history lengths tended to havea similar average number of second-ordercollaborators. In the subject area of medicine in
Brazil, co-authors of women focal authors tended
to show lower connectivity levels compared tocollaborators of men focal authors, and thisdifference widened among those with a longer
publication history. Fluctuating trends in the
average number of second-order collaborators wereseen in business & economics and engineering48
across all regions, and in some cases, collaboratorsof women focal authors had a higher average
number of second-order collaborators than men,particularly in Japan and Brazil. This may be dueto the smaller number of observations in thesegroups, particularly among women (sample size of
networks can be found in Appendix A, Table A.1).
Given that men have higher network centrality
than women (see Figure 4.2), the results
pertaining to second-order collaborators areinteresting. Together, these results indicate that
although women authors tend to connect withfewer collaborators than men on average, theaverage number of second-order collaborators of
women is similar to that of men. In other words,
the direct collaborators of women are as wellconnected as the direct collaborators of men.

48 The number of focal authors was lowest among authors who first published between 1989-1993, particularly in Brazil and Japan, and in the subjects of business & economics and engineering.

Collaboration Networks PAGE 75

FIGURE 4.3

4.3

Average numberof second-ordercollaborators (x-axis) offocal authors, groupedbased on year of theirfirst publication (y-axis),
by region and subject
area.
Values were normalized byaverage values of observations
by region, subject area andbinned focal authors’ year offirst publication. Average values
corresponding to less than 10
observations were excluded fromthe analysis.

BrazilAverage number of
second order collaborators

0.75

1.0

0.75

1.0

Japan

1.25

1.5

1.75 0.75

1.0

1.25

1.5

1.75 0.75

1.0

USA

EU28

1.25

1.5

1.75 0.75

1.0

1.25

1.5

1.75 0.75

1.0

1.25

1.5

1.75 0.75

1.0

1.25

1.5

1.75 0.75

1.0

1.25

1.5

1.75

1.25

1.5

1.75

Group B

Medicine

Group CGroup DGroup EA
B

Biochemistry

C
D
E
A
B

Engineering

C
D
E
A
B

Business &Economics

C
D

GROUP
A

YEAR OF FIRSTPUBLICATION
1989–1993B

1994–1998

C

1999–2003D

2004–2008E

2009–2013

Women
Men

PAGE 76 The Researcher Journey Through a Gender Lens

E

Brazil

Japan

USA

EU28

FIGURE 4.3 TAKEAWAY:

Women and men are similar in the way they are connected to others in their networks throughtheir direct collaborations (i.e., the average number of collaborators of their collaborators).

Gender composition of direct collaborators
Studies have demonstrated that gendercomposition in a collaborative context has
an effect both on collaboration practices andteam performance.49 Network homophily
based on gender status is a relevant aspect ofa collaboration system because co-authorshipconnections are often driven by gender status
inclusion and exclusion processes (i.e., conscious or
unconscious decisions to seek out gender-similar
collaborators).50 When present, such preferences
have implications for women’s downstream
research productivity. The presence of gender
homophily also has implications for the importanceof women’s representation in a field.
We measured the gender composition of focal
authors’ collaborators, calculated as the proportionof focal authors’ collaborators who were women(referred to as the average share of womencollaborators), to provide insight on gender-based
network homophily among researchers.

Figure 4.4 depicts the average share of focal
authors’ direct collaborators who were women,
disaggregated by gender group as a function of
first year of publication, in each of the 16 networks
defined by focal author region and subject.
The results shown in Figure 4.4 strongly suggestthat women authors show a greater tendency tocollaborate with other women than men authors
do, and vice versa (see supplemental data, FigureB.14); this was seen across regions, subject areasand publication history lengths. A homophily
pattern was clearly detected, where authors fromthe same gender group tended to connect toothers of the same gender with higher probability.
These findings corroborate those found in othercollaboration network analyses, including studies ofmen’s and women’s co-inventing ties.51 Our analysis
also revealed that men’s and women’s levels of
homophily tend to be greatest among those withthe least publishing experience (i.e., earlier career
researcher cohorts).

49 Bear, J.B. & Woolley, A.W. (2011). The role of gender in team collaboration and performance. Interdisciplinary Science Reviews, 36(2), 146-153. doi: 10.1179/030801811X13013181961473
50 Whittington, K.B. (2018). A tie is a tie? Gender and network positioning in life science inventor collaboration. Research Policy, 47(2), 511-526. doi: 10.1016/j.respol.2017.12.006

Collaboration Networks PAGE 77

FIGURE 4.4

4.4

Average share of womencollaborators (x-axis) offocal authors groupedbased on year of theirfirst publication (y-axis),
by region and subject
area.

BrazilAverage share ofwomen collaborators

Japan

USA

EU28

0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5Group B

Medicine

Group CGroup DGroup EA
B

BiochemistryC
D

Average values corresponding toless than 10 observations were
excluded from the analysis.

E
A
B

Engineering

GROUP

C
D

YEAR OF FIRSTPUBLICATION

E

A

1989–1993A

B

1994–1998

B

C

1999–2003D

2004–2008D

E

2009–2013

E

Business &Economics

C

0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5

Women

Brazil

Japan

USA

EU28

Men

FIGURE 4.4 TAKEAWAY:

On average across regions and subject areas, authors tend to collaborate more with authors of
the same gender (see also figure B.14).

PAGE 78 The Researcher Journey Through a Gender Lens

International reach of direct collaborators
Scientific collaboration is an increasingly global
endeavor. Research collaborations that span
geographic boundaries facilitate the transfer ofknowledge across national borders. Internationalties broaden the reach of a research programand can introduce new and diverse ideas into
an author’s work. Studies have shown that
research published in collaboration with a greaterinternational author presence receives higher ratesof citation and has positive downstream effects
on the authors’ research career opportunities andresearch programs.52
We therefore wanted to examine if any difference
between men and women exists in terms of
the share of focal authors’ collaborators who
are affiliated with international institutions (i.e.,
institutions not in the same country as the focal
author’s institution). We called this measure“international reach.”
Figure 4.5 shows the share of a focal author’s
direct collaborators who were international,
separated according to gender group as afunction of year of first publication, in the 16
networks defined by focal author region andsubject. The analysis revealed that men and women
authors have a similar share of international
collaborators across cohorts, regions and subject
areas. A possible exception was the EU28, where
women had a slightly lower share of international
collaborators on average than men across all
subject areas. Our analysis treated the EU28 as asingle region, with “international collaborators”
defined as those outside any EU28 country;
however, we found similar results when defining“international collaborators” as those outside thefocal author’s country. We also found evidence ofslightly lower levels of international collaboration
for women in engineering and business &economics in the USA. The data depicted in
Figure 4.5 also shows that authors with longer
publication histories have higher internationalreach. Researchers with a longer publication
history tended to collaborate with co-authors fromother regions more often than more early career
researchers did. These findings contrast with theresults from Elsevier’s 2017 report,53 which foundthat women were less likely than men to collaborate
internationally on research papers because ourmethodology in 2017 used publications rather thanauthors as the unit of analysis.

52 Aksnes, D. W. (2003). Characteristics of highly cited papers. Research Evaluation, 12(3), 159-70. doi: 10.3152/147154403781776645
53 Elsevier. (2017). Gender in the Global Research Landscape. Retrieved from: www.elsevier.com/research-intelligence/campaigns/gender-17. Accessed October 23, 2019.

Collaboration Networks PAGE 79

FIGURE 4.5

4.5

Average shareof international
collaborators (x-axis) offocal authors where thelatter are grouped basedon year of their firstpublication (y-axis), byregion and subject area.
The share of international
collaborators is computed as
the ratio of the count of direct
collaborators not affiliatedin the same country and/or
region as the focal author tothe overall count of their direct
collaborators. The EU28 wastreated as a single region, with“international reach” defined ascollaborations beyond the EU28.
Average values corresponding toless than 10 observations were
excluded from the analysis.

GROUP

YEAR OF FIRSTPUBLICATION

A

1989–1993B

1994–1998

C

1999–2003D

2004–2008E

2009–2013
Women
Men

PAGE 80 The Researcher Journey Through a Gender Lens

BrazilAverage share ofinternational collaborators

Japan

USA

EU28

0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5Group AGroup B

Medicine

Group CGroup DGroup EA
B

Biochemistry

C
D
E
A
B

Engineering

C
D
E
A
B

Business &Economics

CDE

0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5 0.0 0.125 0.25 0.375 0.5
Brazil

Japan

USA

EU28

FIGURE 4.5 TAKEAWAY:

Women and men authors in most regions and subject areas are similar in terms ofinternational reach, with the exception of EU28, where men have slightly more international
collaborations than women.

Expert Interview

Sarah Sharples, CErgHF, FIET, FIEHF, PhD,
MSc,BSc (hons), PGCAP
Pro-Vice-Chancellor for Equality, Diversity and Inclusion
University of Nottingham

How would you describe the current
state of gender diversity in research,compared with 5 years ago, and its
impact on research and/or researchers
globally and/or in your region inparticular?
One of the biggest changes I’ve seen in thelast five years is an increased awareness ofgender diversity with regard to leadershipand in research teams. From an engineeringcontext, we know that women are significantly
underrepresented in general, and in particularamong leaders of research teams. There is a lot
being done to address gender diversity at the PhD
and postdoctoral stages, but these efforts haven’t
moved up the career ladder to have an impact
at the research leadership stage. I think we arestill seeing significant bias toward men in STEM
research, and though gender issues come throughless strongly in the arts and social sciences,
they are still present. So I would say there has
been progress made in terms of the awareness ofgender issues in research and their importance,
but I haven’t seen a significant change in terms of
the actual makeup of research teams to the extent I
hope we will see in five years’ time.

Are there initiatives, policies, orinterventions that have emerged withinyour region and/or field in the last
3-5 years that you feel have impacted
progress and should be monitored toassess impact?
There are two examples. The first are changes
in research fellowship recruitment programs,
such as the UKRI Future Leadership fellowship
program, which considers all aspects of diversity,
not just gender. My colleague, Jessica Corner, wholeads the research fellowship recruitment here
at Nottingham, has made significant inroads inexamining and exploring both gender and ethnic
diversity and potential bias at all stages within
the recruitment process, from the criteria tocommunication and advertising to mentorship.
Her work was featured in the recent UKRI reportas an example of good practice in this area. These
fellowships are competitive and prestigious, so

incorporating diversity in our recruitment process
is in no way about positive discrimination, it isabout positive action to encourage applicants fromas many diverse groups as possible. In doing so,
we create an incredibly diverse pool from which toselect fellows. We are also very careful in making
sure the interview process itself is not biased; forexample, we look at quality of publications rather
than quantity to account for applicants who may
have taken time off for maternity leave. We alsodeliberately attract people with care responsibilities
by providing opportunities and funding forchildcare during the fellowship period.
The second example is at the other end of the
career ladder—promotions criteria. Within
universities, promotion criteria are fraught
with myths; for example, that you must have
X number of publications or a certain level offunding to become a professor. Many universities
are trying to address bias in promotion byemphasizing teaching, public engagement, andentrepreneurship as well as research activities andfocusing on the quality of publications rather thanquantity. The goal is recognizing that there are avariety of paths that people take to do excellent
research and we need to make sure that everyone
is assessed fairly.

What value do data and an evidencebase offer as tools to policymakers andinstitutional leaders to address issues ofgender diversity and equality?
Data—both quantitative and qualitative—are
hugely valuable in identifying where disadvantage
is happening and prioritizing where we should
be intervening as leaders, policymakers, andfunders. The top-level quantitative data tells us
what is going on, and the qualitative data can help
us understand why, by providing real-life examples
illustrating the multiple factors that interact toproduce the systemic disadvantage that womenexperience in research. In the report, the summaryof the qualitative data along the four quadrants
of opinions that people might have—whether
the system is fair or biased and whether genderbalance is or is not a high priority—was a really
elegant articulation of some of the challenges togender diversity. I was particularly interested in
the “fair-minded women” and “indifferent women”

Expert Interview PAGE 81

I had a really supportive PhD supervisor
who absolutely supported me andrecognized when I needed a little more
confidence to demonstrate my role as aleader within the research team.
groups. Some women, perhaps understandably,
feel that they have successfully worked througha very difficult and biased system on their own
merits and they never want to feel that they would
be seen as having been given an unfair advantage
because of their gender. While the report’s data
can be quite dispiriting, it nevertheless gives us astarting point for conversations within our researchcommunities about what needs to change.

Given the diversity of perceptions on
gender issues, what do you consider themost important factors that influence
progress toward equality for men andwomen in research?
Looking at my colleagues, particularly women,
who have successful careers in research, themost common factor is that they have had
support, often from a research leader. I had areally supportive PhD supervisor who absolutely
supported me and recognized when I needed alittle more confidence to demonstrate my role
as a leader within the research team. When I talkto colleagues who have had more difficulty intheir careers, it is often because they lacked thatmentoring, that external support from colleagues.
Now that I am in a senior position, I try toconsciously support people as they pursue theirresearch careers. It’s not altogether a selfless act,
because when your colleagues are at their best, theentire research team benefits. But being a really
good leader is about helping others rise.

What information or insight fromthe report do you find particularlyinteresting and important forpolicymakers and institutional leaders
to consider in relation to your region or
specific subject areas?
The sexual harassment and misconduct issues—that unacceptable behaviors are still being
tolerated or accepted and that they are having asignificant and lasting impact on some women’s
research careers—was really upsetting, but
important to recognize.

PAGE 82 The Researcher Journey Through a Gender Lens

I was also struck by the networks data because
we do know that building networks often requires
national and international travel. I made theexplicit decision when my children were young
not to travel internationally. The decision led me
to become more involved in EPSRC and doctoral
training as I worked more on building my national
profile and research network. I thought—probably
wrongly—that this strategy would have less ofan impact on my homelife, but it worked out
pretty well. But that decision also likely shaped myresearch network so that it looks different fromthat of a colleague who did not have similar care
responsibilities.

In the report there are trends identified
from scientific publications, which areconfirmed for both awarded grants andeven more so when analyzing patents.
What does this say about the genderinnovation gap?
I absolutely recognized the gender gap interms of grants, patents, and entrepreneurship.
At Nottingham, we are working to encourage
women to apply for more grants, particularly
large grants. Once women apply, they have areasonably equal chance for success as men, but
the absolute number of applications remains lower
for women. Because there are fewer of the larger,
more prestigious grants, the underrepresentationof women is even more apparent there. This
also means that there are fewer women in
strategic policymaking discussions, presenting toparliamentary scientific committees, or engaging
with government departments.
Colleagues at Nottingham recently led an event
as part of a consortium of universities to establish
a network for women researchers who areinterested in entrepreneurship and innovation.
We discussed why fewer women might beengaged in entrepreneurship, including a lower
willingness to take risks, the greater time demands,
especially when added to an already demanding
academic research career, and the lack of womenrole models. We hope that the new network willaddress some of these challenges.

What impact do you think, if any, the#MeToo movement has had on theworld of research?
The sexual harassment and misconduct
experiences that are being described by the#MeToo movement are important to address in
the research environment, but I’m not sure howmuch of an impact it has made. Just one incidentof sexual misconduct or harassment is one toomany. If the #MeToo movement has made people
feel more confident or more trusting in sharing
their experiences and raising awareness, then thatis valuable. Working in the fields of engineeringand technology, I have observed these issues more
often through online communications and online
collaborations. I feel that such issues would nothave received as much attention if it wasn’t for the#MeToo movement.

Thinking about the future of gender
diversity and equity in research globally,
where do you think we’ll be in 10
years’ time and what organizationaland or cultural issues do you think will
influence change most significantly?
I think we are heading in the right direction, but
it’s going to take more than 10 years to achieve
something that looks like gender equity. First, weneed to address issues around gender disparity
starting at primary and secondary school. For
example, children who are exposed to maths early
and throughout their school years are more likely tofeel comfortable engaging a career in engineering.

We also need to make sure that women are treatedfairly, academically and professionally. We need towork with the research community to find practicalways to make changes that move us toward gender
equity. Routine reporting of pay data and routinereflection on that data is incredibly important.
It’s not just about paying women more, it’s about
how to create a fair pay structure that reduces thegender pay gap.
We are also making significant progress on
the ability to discuss topics like gender, care
responsibilities, and protected characteristics inresearch, but there needs to be a conversation
about the intersectionality of gender, disability,and ethnicity, and how these together have moreof an impact on successful progression through a
research career. Being able to ask for reasonableadjustments—for example, allowing meetings
to be joined remotely rather than requiring
international travel, or accommodating thechanging health care needs of team members—
will allow everyone to do their best.
Finally, while we are making progress in theseconversations, we also need to recognize that
there is still resistance to gender diversity andequity, primarily because of a lack of knowledge.
This report is incredibly useful for increasing
knowledge in a non-threatening, data-driven way.
Overall I am hopeful, but there is still an awful
lot of work to do. We recognize the enormity ofthe task and the role we can all play in enabling
everyone to participate and bring diverse ideas
together to strengthen research.

Finally, while we are making progress inthese conversations, we also need torecognize that there is still resistance togender diversity and equity, primarily
because of a lack of knowledge.

Expert Interview PAGE 83

Collaboration Networks

Conclusion
We conducted a network analysis based on alarge set of Scopus publications to examine
men’s and women’s collaborative research
activities. This study included a cohort of focal
authors from 16 selected region-subject pairs.
We further focused our attention on an author
set from a single year (2013) and examined theircollaborative activities across a five-year window(2009-2013). Our exploratory network analysis
describes the characteristics of men and women
researchers’ collaboration activities in theseregions and subject areas.
We found that, across several regions and subject
areas, men tended to have more co-authors
than women and this difference widened amongauthors with a longer publication history. Thisdata suggests that the higher network centrality
among men authors may be an underlying factor
driving the higher average publication output
observed among men compared to women authors(in any authorship position; see Figure 2.1).

PAGE 84 The Researcher Journey Through a Gender Lens

However, we also found that women andmen were more similar in the way they wereconnected to their potential collaborative space(to second-order collaborators) through theirdirect collaborations and with respect to theirshare of international collaborators (with the
exception of the EU28, where men authors had aslightly higher tendency to establish international
collaborations than women authors). We also
found that women authors tended to collaborate
more with women than men on average while men
collaborated more with men than women acrossregions and subject areas.
Future work could broaden the scope of themeasures and time periods used and include
more regions and subject areas. For example, thecollaboration network characteristics studied here
were limited to a five-year time window, which
could be expanded in future analyses. In addition
to the metrics considered here, future studies
could make use of more sophisticated metrics
that a network analytic perspective can provide.
It would also be relevant to investigate how
network-based indicators revealed in this dataset
relate to an author’s future productivity and othercareer outcomes.

Chapter 5

Researcher
Perspectives
Perceptions about gender-related issues in academia

Key Findings• Researcher attitudes towards gender diversity
and equity vary widely among men and women.
Most of the differences in viewpoints are related
to the importance an individual places on genderbalance and to the perception of fairness in theacademic system.
• There are two opposing opinions on the causesof gender imbalance and inequality in academia.
Some groups (men and women) attribute genderinequality to the attitudes and ambition levels of
women. Other groups attribute gender inequality
to a systemic and cultural (unconscious) bias
against women.
• Researchers perceive that family duties can havea negative impact on research careers ( for both
women and involved men).
• Researchers suggested interventions to increase
gender balance and equity that reflect theirperception of causes of the gender inequality.
Those suggested are either aimed at increasing theassertiveness and self-confidence of women or atchanging the male-dominated culture and reducing
the possibility of (unconscious) bias.
• The lack of consensus over a single bestintervention may be interpreted as a lack of a“one size fits all” intervention.
• Additional research is needed to understand theviewpoints from women and men researchers
who are indifferent to the gender equity discussion
and from men who are negative about current
interventions that they perceive discriminate
against men.

Researcher Perspectives PAGE 87

Researcher Perspectives

Introduction
5.1
The analysis of quantitative data in the previous
chapters revealed various gender-based
differences in research participation, researcher
footprint, publishing continuity, author mobility,
and collaboration patterns. In this chapter, we
present the results of additional research to provide
a deeper understanding of researchers’ uniqueexperiences and perceptions of issues related togender in research. This qualitative research serves
to illustrate the diverse viewpoints of researchers
related to gender diversity and equity. It aims toprovide insight into the differences in perceptions
and attitudes on gender-related issues in academia
such as the importance of gender diversity or
equity, the factors believed to contribute to alack of gender diversity or equity and potential
interventions to support greater gender diversity inthe future. Some of the collected stories may serveas starting points for new hypotheses and inspire
future investigations. A detailed description of themethodology can be found in Appendix A section“Qualitative Analysis.”

Online survey among
academics worldwide
to understand what
opinions exist

Create clusters ofsimilar responses

Recruit representative
participants from eachcluster to interview

Define main themes
based on opinions
and experiences ofparticipants

FIGURE 5.1

Overview of the qualitative researchmethodology: using survey results
to define categories, then recruiting
participants from each category forinterviews.

PAGE 88 The Researcher Journey Through a Gender Lens

Researcher Perspectives

Analyzing the Diversity ofOpinions on the Role of
Gender in Academia
To understand perceptions and attitudes ofresearchers about the role of gender in academia,
we first conducted an online survey that was sent
to researchers working in various subject areas
and geographic regions (see Appendix A, section“Qualitative Analysis - Preliminary survey”).
The respondents included researchers from the
Elsevier Advisory Panel,54 as well as researchers
contacted through social media channels. The
survey included various statements about gender
diversity and equity in academia related tocareer progression, the workplace and personal
experience. The participants were asked to indicate
their level of agreement or disagreement witheach statement in a set of closed-ended questions
as well as respond to a series of open-ended
questions. We collected 423 valid responses fromthe online survey, of which 257 had complete
responses to the open-ended questions.

Based on the survey results, we defined eightclusters of survey answers with related pointsof view on gender (see Appendix A, section“Qualitative Analysis - Defining respondent
clusters”). To get a better understanding of thevarying viewpoints and the personal experienceswith gender issues, we interviewed 25 researchers
who had provided open-ended responses in the
online survey that most closely represented eachof the eight clusters. Our goal was to recruit
equally from the different clusters of perceptions;however, we were unable to reach any researchers
who gave survey responses representative of threeclusters: “indifferent men,” “indifferent women”
and “indignant men,” and we interviewed only one
researcher within the category of “aware women.”55
The interviews focused on the differences inperceptions on gender issues, reflecting theopinions from the eight categories that were
defined based on the online survey. See figure 5.1
for an outline of the methodology described inthis chapter.

54 The Elsevier Advisory Panel is managed by Elsevier (Customer Discovery & Innovation) for user research purposes. The Panel comprises more than 3000 researchers from around theworld, across disciplines and career levels.
55 Although we did not interview any researchers with survey responses from these clusters, some of our interviewees did share their impressions from peers who represented opinions
representative of the clusters “indifferent men/women” and “indignant men.”

Researcher Perspectives PAGE 89

Grouping researchers’ perceptions based on
attitudes and experience
We observed a wide variety of perceptions inthe survey among men and women, both inagreement and in disagreement with statements
pertaining to equal career opportunities for
women and men. Based on the answers to bothclosed- and open-ended questions, there were twomain parameters along which people’s attitudes
differed. These were:• The degree to which there was agreementthat gender balance in academia is important(gender balance was not considered to be thesame as gender diversity)56• The degree to which there was agreement thatthe current academic system is fair to both
women and men
Additionally, we also identified specific contextual
parameters based on varying personal experienceamong the respondents that related to:• The personal experiences of men and womenin combining an academic career withparenthood• The personal experiences of men and womenin gender-biased career situations, either theirpersonal experience or observations of theirpeers’ experiences• The current environment and gender policies
at their institutions• Some social, cultural and economic
differences that affected people’s experiences
and perceptions (e.g., generational gaps,
cultural/religious expectations on the roleof women as caregivers, education of girls/
women and boys/men to behave in certain
ways, the legacy of political ideologies andeconomic influences)
In trying to capture this wide variety of attitudes
and personal experiences, we defined eight clustersof survey answers with related points of viewon gender in academia (Figure 5.2). These eightclusters were based on similarity of opinions on
gender-related issues as expressed in the openended survey questions and do not represent
homogeneous groups of people. The clusters wereclassified along the two main attitude parameters(axes)—importance of i) gender balance and ii)
fairness—and by certain personal experiences. Thissection explains the two attitude parameters andthe experience factors.

56 Respondents distinguished between gender balance and gender diversity, with gender balance referring to equal numbers of both men and women and gender diversity referring
to representation of both genders.

PAGE 90 The Researcher Journey Through a Gender Lens

FIGURE 5.2

Overview of the eight clusters of different points ofview on based on the survey results, aligned along thetwo main parameters evaluated.
Gender balance is importantFair-minded men

Open-minded men• Willing to change the culture/system• Willing to share childcare responsibility• Agree that the goal should be to have moregender balance• The system is fair, but there are some“natural” reasons for the imbalance

Discouraged women
Fair-minded women• Experienced career bias or missed
opportunities• It can be hard as a woman, but they just need
to be tough• Maternity has set career backAcademic system is fair

Academic system is biased

Indifferent women

Aware men / women• Main concern is avoiding discrimination• Gender balance is not the main goal

Indignant men• Experienced career bias in favor of women• Feel that system is changing to be unfair
towards men – now they are the ones being
treated unfairly• No personal negative experience with gender(gender-positive environment)• OR: less career ambition

Indifferent men• Strong belief in current system of
meritocracy• Other issues are much more important

Gender balance is not a high priority

Researcher Perspectives PAGE 91

The importance of gender balance
The survey revealed differences in the perceptionof gender issues reported by men and women, as
well as differences in perceptions among men andamong women. When asked about the importanceof gender diversity in the research workplace, most
women (90%) and most men (62%) answered that itwas extremely or very important (Figure 5.3)

The viewpoints on the importance of genderbalance varied. In our interviews, several men
and women recognized the benefits of gender
diversity and balance. These individuals cited thepositive impact of diversity on science, the diversityof topics that result from increased diversity
and gender balance and the more pleasant work
environment and positive cultural shift that result
from increased diversity and gender balance(Figure 5.4, upper quotes). There were also men
and women who were not concerned with genderbalance, arguing that there would be no effect on
the quality of research at all and that it should bea matter of personal choice to pursue a career inacademia. There were some men who thought
there was too much attention given to the matterof gender diversity; these were often men who had
experienced discrimination in their careers (Figure
5.4, lower quotes).

5.3
FIGURE 5.3

Responses to thesurvey question, “Howimportant is it to havegender diversity in the
research workplace?”

Percent

0

10

20

30

40

50

60

70

80

90

100

0

10

20

30

40

50

60

70

80

90

100

Extremely important
Very important
Somewhat important
Not too important
Not important at all

Women
Men

PAGE 92 The Researcher Journey Through a Gender Lens

Percent

FIGURE 5.4

Representative quotes from the online survey from eachof the eight viewpoint clusters in relation to the parameter“the importance of gender balance in academia.”
Gender balance is important

Open-minded men“I find women easier to work with, as with somemen there often are problems with too many (selfassumed) ‘alpha-males,’ women are a lot more stableand dependable to work, and in my opinion caremore about the work and less about themselvescompared to some men who care mostly about theirown stature.”

Fair-minded men“Gender diversity provides the opportunity for
different and important viewpoints that often differ
from that of men, which is sorely lacking in malebiased environments.”
Man, UK, postdoctoral fellow : medicine & life sciences

Man, UK, postdoctoral fellow : medicine & life sciences

Fair-minded women
Discouraged women“We need to change the culture of leadership –you can only do that if there are more women in
leadership positions.”“There should “naturally” be diversity, not a forced
one. This leads to views such as, “Oh, she got theposition because of gender diversity.”
Woman, Italy, postdoctoral fellow : physical sciences

Woman, UK, midlevel career : medicine & life sciences

Indifferent women
Aware men / women“Gender equity is really important and fair, but I
personally don’t think that gender diversity is SO
important: if a lab is made of only female, only
male or mixed, don’t change its quality. I think thatwhat is important is that good workers are selected
and fairly treated for their skill and passions, andnot selected for gender or race...”Man, US, postdoctoral fellow : medicine & life sciences“Woman’s choices: not all woman want to beresearchers! I think the matter is overrated. Woman
do what they want, choose what they want, havetheir own tastes and priorities.”
Woman, UK, early career: medicine and life sciences“Too few of us are concerned since other priorities
are generally put forward, e.g., financial.”
Woman, France, senior career : medicine & life
sciences

Frustrated men“Gender diversity is just another artificial problem
in science.”
Man, Poland, mid career : social sciences

Indifferent men“I’ve never paid attention to how much attention isbrought to the subject.”Man, US, postdoctoral fellow : physical sciences

Gender balance is not a high priority

Researcher Perspectives PAGE 93

Perceptions of fairness of the academic system
The online survey included several questions on
the perception of equal career opportunities formen and women in research. For instance, we
asked about the level of agreement with statements
about the opportunities women have compared
to men to obtain entry-level research positions
and tenured positions, to lead research teams or
to work in administrative leadership positions.
The answers revealed that, in general, women
have more negative viewpoints on the career
opportunities for women, whereas men have morepositive viewpoints on career opportunities for
women. This is consistent with previously publishedfindings.57 In our survey analysis, we used a proxy
to measure the perception of bias against womenin their research careers, asking whether women58
need to work harder than men to be consideredgood at their job (Figure 5.5). The responses to thisquestion made it clear that women and men differ
in their perceptions of gender bias in research, andthat there is disagreement among men and womenwith regards to the impact of bias against womenin their research careers.
In the open answers the viewpoints on the fairnessof the system were very diverse too. Figure 5.6
shows quotes from both men and women who
feel that the rules of the academic system are fair
and that there are equal opportunities for men
and women. The opinions about the system notbeing fair were very diverse. They were either basedon observations or on personal experience of bias
against women or against men.

5.5

FIGURE 5.5

Strongly Disagree

Survey responses tothe statement, “In myorganization, women
have to performbetter than men to beconsidered good at theirjob,” by gender andsubject area.

Disagree
3% 11%

SocialSciences

NeutralAgree

Strongly Agree

14%

43%

29%

Women
Men

20%

Physical Sciences,
Technology,
Engineering andMathematics

29%

29%
8% 3%

32%

32%

18%

24%
3%

16%

17%

6%

36%

35%

10% 3%

11%

42%

28%

Medicine &Life Sciences
17%

33%

20%
7%

7%

17%

7%

13%

40%

40%

Arts &
Humanities

Strongly Agree

33%

Agree

67%

NeutralDisagreeStrongly Disagree

Strongly Disagree

Disagree
3% 11%

SocialSciences

NeutralAgree

Strongly Agree

14%

43%

29%

Women
Men

20%

29%

29%
8% 3%

Physical Sciences,
Technology,
Engineering andMathematics

17%

18%

6%

36%

35%

32%
32%
24%
10% 3%
57 Garcia-Gonzalez, J., Forcen, P., & Jimenez-Sanchez, M. (2019). Men and women differ in their perception of gender bias in research institutions. SocArXiv. Retrieved from: https://
osf.io/preprints/socarxiv/pr5ec/. Accessed December 6, 2019.
58 We did not ask if men need to work harder than women to be considered good at their job.

3%

16%

11%

42%

28%

Medicine &Life Sciences

17%

PAGE 94 The Researcher Journey Through a Gender Lens

33%

20%
7%

Arts &
Humanities

7%

7%

17%
40%

13%
40%

FIGURE 5.6

Representative quotes from the online survey fromeach of the eight viewpoint clusters in relation to theparameter “the fairness of the academic system.”Fair-minded men“Cohorts of older male researchers still have bias,
which influences decision making (directly andindirectly).”Man, UK, postdoctoral fellow : medicine & life sciences

Discouraged women“I have inhibited myself from applying for a full
professorship position on the belief that I will berejected even while having more merit than others
and thus will have to wait five more years to apply
again. I think the commission will act subjectively
and not on merit-based criteria.”
Woman, Chile, early career : medicine & life sciences

Man, Egypt, senior career : medicine & life sciences

Fair-minded women“I have been professor, researcher, coordinator of
postgraduate program, research advisor, mother,wife....I suppose my gender, in my career, did not
impact my professional activity.”
Woman, Brazil, midlevel career : physical sciences

Academic system is biased“Personally, I do not let discrimination, either
negative or positive, step in my career. I just do
my work to do my best. I am over 50, female andindigenous. So there is age, gender and racial bias
in my way.”
Woman, Ecuador, senior career : physical sciences

Indifferent women
Aware men / women“It is hard to know if and to what extent being
privileged has helped my career. I would like tothink it hasn’t, but there is always a chancea woman in my position wouldn’t have gotten
my job.”Man, UK, postdoctoral fellow : physical sciences

Indignant men“At times women are even considered more thanmen. If a man and a woman are competing forsomething, priority is given to the woman than theman.”
Man, Ghana, predoctoral candidate : social sciences“I’ve never had any problems by gender. I havealways been evaluated based on my competence.”
Woman, Brazil, doctoral candidate : social sciences“I think in research what should matter ismeritocracy, independent of gender.”Woman, Australia, postdoctoral fellow : physicalsciences

Indifferent men“Usually every laboratory has around the same
number of men and women. I don’t see any
particular attention in doing so, it is simply that
men and women are equally good, and during
the time the laboratories tend to have the same
number of people of both genders.”
Man, US, postdoctoral fellow : medicine & life sciences

Researcher Perspectives PAGE 95

Academic system is fair

Open-minded men“The laws and bylaws do not differentiate between
men and women. Gender insensitive performanceindicators are applied at any phase of appointment,
promotion or funding.”

Perceptions on how gender influences
researchers’ academic careers
In our interviews with 25 survey respondents, we
further examined the personal experiences andthe influence of these experiences on researchers’
opinions about the role of gender in academia. We
explored differences in perceptions and personal
experiences in a range of aspects of the academic
career, including recruitment, promotion, salary,
publishing, citation practice and funding. We
mapped the interview findings to the eight clusters
defined in the survey; here, we illustrate thesedifferences in opinions and experiences using
quotes from the interviews.
The interviewees also reported observing greater
gender diversity at the early-career level and lessgender diversity among more senior leadership
positions, such as group leaders, tenured professor
positions or senior administrators.
The perceptions on the topic of career
progression of women in academia were very
diverse (Figure 5.7 and Table 5.1 overleaf ). Someinterviewees attributed the lower proportion of
women at senior levels to the tendency of women
to be less self-confident and lacking in ambition.
Others saw unconscious bias as an important cause
for lack of career progression. Finally, there wasalso an impression that the competitive and moredemanding culture at more senior levels were lessattractive to women, resulting in more women not
aspiring to pursue these roles.

PAGE 96 The Researcher Journey Through a Gender Lens

PERCEPTIONS OF THE CAUSESOF LOW REPRESENTATION OF
WOMEN IN STEM
Our survey results confirmed theperception that there are relatively
fewer women working in STEM (science,technology, engineering and mathematics)
than in other fields. When researchers wereasked about the factors that contribute to thelower participation of women in STEM, theresponses varied. Numerous respondents
indicated that women are not encouraged
enough during primary or secondary
education to engage in more technical fields.
One respondent also suggested that not
many women would be interested in the
more physically demanding work in STEM
fields, for example, working on overnight
experiments and going on field expeditions.
Both men and women reported that it can bedaunting to be the only woman in a working
environment, and that women might prefer
to work among other women.
One explanation given for the lack ofgender diversity was that the low numberof women role models in STEM gives
the impression that there are fewer
opportunities for women. Based on current
experience, some researchers suggested
that if an institution actively creates
opportunities for women to progress intheir STEM careers, there will be more
women role models and the field might
become more attractive to other women.

FIGURE 5.7

Representative quotes from interviewees on their attitudes about the career
progression of women in academia, categorized according to the different
viewpoint clusters and in relation to the two main parameters analyzed.
Gender balance is importantFair-minded men

Open-minded men“I have a position in my group and it’s only for females, so I
have no problem on this and actually there are two very goodcandidates that are male, that I know personally but okay.
They will find another position.”Man, Netherlands, professor : physical sciences“Because of the way women are raised, and also the factthat the leadership is mainly male leadership, they havevalues that are not necessarily...where professional women
do not fit.”
Man, China (from EU), lecturer : arts & humanities

Fair-minded women“Sometimes the way that you have to behave in order to be
successful isn’t in line with our values, and how we want tobehave professionally. And so we actively would make thechoice to take ourselves out of that. And not to be involved
in it.”

Academic system is biased

Woman, UK, midlevel administrator : medicine & life sciences“I know I’ve been disadvantaged because my head of
department refused to support my promotion, and initiallyI listened, and then I got stubborn and went about it
independently, which was much harder. But I eventually, I
did get promoted in that round of promotion.”
Woman, Australia, professor: physical sciences

Academic system is fair

Discouraged women

Indifferent women
Aware men / women“There probably is overall [gender balance], but I think you
probably see more positions of power held by men. There’s
more female Vice Chancellors across the faculty – In the
more let‘s say the professional service or the administrative
type roles I think women sort of dominate that side ofthings…”
Woman, UK, professor, administrator : physical sciences“But from the work point of view, in terms of career
progression, no, not every woman does want to progress into
senior roles. And I’m not necessarily sure that I do...”Woman, UK, midlevel administrator : medicine & life sciences

Indifferent men“Men do not make it to the top by mere wishing and taking
advantage for being men. They worked hard and hard
everyday to get there. So women should try hard and havehope that they will be there one day.”
Man, Ghana, PhD candidate : social sciences*

Gender balance is not a high priority* Indicates quote is from open-ended survey response

Researcher Perspectives PAGE 97

TABLE 5.1

Reasons given by survey respondents and interviewees for the lack ofcareer progression among women researchers

Attitude:
Women lack ambition/skills

Attitude:
Women lack opportunity, possibly due to bias

Examples:Examples:• It is too difficult to combine a time-consuming careerwith children• Some men think women are less intelligent(unconsciously), therefore• Some women are content to just do research and notseek a leadership positiono Women need to work harder to prove themselves
o Women are being patronized and not getting thesame attention from supervisors• Women are not competitive or assertive enough forsenior leadership positions• Women feel more insecure and strive for perfection
before applying for position• Women do not deal well with the frequent rejections inacademia (funding, publications, promotions)• Women need to develop new skills to be researchleaders and need to be strong to deal with the
responsibility

o Women are not considered for promotion orawarded grants so they can lead a group• Historically, the characteristics that are valued forleadership positions have been defined by men. Womenmight have other characteristics, but these are notconsidered valuable in leadership positions.

Perceptions on differences in salary
Most interviewees said they were not aware of their colleagues’ salaries. We observed that researchers
who perceive that the system is fair also expected salaries to be equal for men and women in the same
positions, especially if the salary structures were shared openly. Conversely, lack of transparency in pay wasmentioned as a contributor to pay disparity.

“

I mean anything I’d say on salaries, that we have found the key issue is generally in loadings [extra
payment employees may be entitled to on top of their usual pay], and negotiation of loadings,
which again, tends to happen in an opaque manner, they’re not transparent. So there is a level ofaspect where men tend to enter maybe on the second step of the salary because they negotiate that,
whereas women tend to enter on the first step of their salary. So you get a big disparity there, butthen when it comes to loadings, there's huge disparity. And so the easiest way to deal with that is justto make that entire process transparent.”
Man, Australia, senior administrator : social sciences

Some interviewees who perceived the system to be biased mentioned negative situations regarding thesalaries for women researchers. However, these tended to point to difficulties for women in reaching thesame position (level), rather than to differences in pay between colleagues at the same level.

“

In general, it’s still harder for women to get the same position as the men and they have the gender
pay gap. So men get paid better for the same position than women.”
Man, Germany, postdoctoral fellow : medicine & life sciences

PAGE 98 The Researcher Journey Through a Gender Lens

Perceptions of gender bias in recruitment
and promotion
Unconscious bias in recruitment and promotion was mentioned as a potential cause of gender imbalancein the working environment. In the active researchers survey, 38% of women (and 13% of men) said there
is a lack of gender balance in their field because there is bias or discrimination in recruitment, hiring andpromotion processes. (Figure C1)
Based on the responses to open-ended questions in the online survey and the interviews, wesummarized the factors that were suggested as contributors to bias against women in recruitment andpromotion in institutions:• Job postings that included gendered words might dissuade women from applying for the position• Networks of mainly men professional contacts (or recruiting agencies) that are asked to suggest
talent, resulting in a lack of women representation on recruiting shortlists• Promotion committees in the university that consist of predominantly men and prefer masculine
leadership characteristics• After-work socializing to build personal network, which is more common among men than women• Women more likely to hold off applying until they are past the point where they could have received
the promotion• To be able to lead a research team, it is necessary to win funding. If grant applications are notanonymous they are open to gender bias.
• Less frequent conference attendance by women that restricts opportunities to establish collaborations• Fewer invitations to be keynote speakers or serve as panel members at conferences• Women tending to be asked to do supporting tasks, such as sitting on committees or organizing
events that take away from research work and are not part of the evaluation for promotion

Researcher Perspectives PAGE 99

Impact of family on research careers
When asked about the impact of family on
research careers, interviewees responded thatthey felt that having children and the availabilityof maternity leave and childcare support have asignificant impact on both men and women as
well as gender diversity in research. Both men andwomen reported that having children could cause adelay or change in career opportunities.
Overall, most of the researchers we interviewed
agreed that maternity leave and childcare duties
can have a negative impact on women researchers’
career progression (Figure 5.8). Women were more
likely than men to report taking on the main shareof childcare compared to their partners. There
were also women who had successfully navigatedhurdles in balancing their family life with theirresearch careers. They described the need to be very
efficient and having to be comfortable entrusting
their children to others (e.g., grandparents,
childcare workers, nurses).

PAGE 100 The Researcher Journey Through a Gender Lens

In Elsevier’s active researcher survey (see Appendix
A, section “Researcher Survey”), 45% of women
researchers felt that balancing their personal life
with their career is one of the biggest barriers totheir career progression (Figure C.11), and women
were more likely to leave their career in researchdue to family commitments (Figure C.5).
Our interviewees pointed to different aspectsof academic jobs that can worsen the impact ofchildcare duties on career progression:• The need for greater job security and more
flexible hours after having children• The prevalence of short-term contracts,
especially when the maternity period
coincides with the end of the contract• The practice of long work hours and the
expectation that working part time will havenegative career consequences• Lab-based research is not as accommodating
to flexible working hours and locations• The high cost of childcare coupled with little
support from universities

FIGURE 5.8

Representative quotes from interviewees on the impact of family life
on research careers, categorized according to the different viewpoint
clusters and in relation to the two main parameters analyzed.
Gender balance is important

Open-minded men“There’s enough childcare help and enough opportunities
for fathers to step up and do more work. I’m a good
example of that...it’s challenging in order to balance your life
and work as much as it is for women, but I didn’t feel that
I was harmed in my career because of having to do morewith my family.”Man, UK, research associate : physical sciences

Fair-minded men“…the condition is the woman has to find a job that’s parttime, to have enough time for her children.”Man, Greece, postdoctoral fellow : physical sciences

Fair-minded womenAcademic system is biased“I think I’m frustrated because I feel that having had mytwo children and two periods of maternity leave and being
part-time has been disadvantageous in terms of progression
because it makes it really, really difficult to tick all the boxes
that I would need to tick in order to progress.”“I love being a mum. But my professional identity, my careeris important to me too. And I think that my husband and I
should be a team on it. And therefore, if he’s the one whotakes the lion’s share of the work, that’s absolutely fine byme, as long as one of us is doing it, and one of us sees thatas work, and values that, and does it properly.”
Woman, UK, midlevel administrator : medicine & life sciences

Woman, UK, midlevel administrator : medicine & life sciences

Indifferent women“[Some women] want to put child-rearing first...and that
affects their career progression. And they’re absolutely happy
with that because that’s what they want.”

Aware men / women“You’re working at the lab and get papers and stuff like that.
And if you took time out to have a child, I imagine it would
be really very difficult and a lot of pressure, as a woman, I
mean, yeah. And, as a man, I know I don’t have to face thatchoice... I can make a choice to not go to work as much, but I
don’t have to do that. I mean, I would be willing to make thatchoice, but I don’t have to. It’s not forced upon me by thesituation [as is the case with women].”Man, UK, postdoctoral fellow : medicine & life sciences

Woman, UK, midlevel administrator : medicine & life sciences

Indifferent men“…if you hire a woman of a certain age, they’re going
to leave to have children, and this is detrimental to yourbusiness. As a PI, this would be something that they would
think about, and would cross your mind, whether you act
upon it or not. It would definitely be in the back of yourmind.”
Man, UK, postdoctoral fellow : medicine & life sciences

Gender balance is not a high priority

Researcher Perspectives PAGE 101

Academic system is fair

Discouraged womenImpact of gender on research outputs: funding,publishing, citation
In our interviews, we discussed perceptions of gender bias in current funding, publication andcitation processes (Figure 5.9). In general, the current publishing and citation system was perceived to
be fairer than the academic career system; in other words, the negative attitudes towards the fairnessof the academic system was not reflected in the attitudes towards the publishing system. Many of ourinterviewees were editors or peer-reviewers themselves. They said they would not let the gender of theauthor affect their decision to publish. Furthermore, they said most publications have multiple authors ofboth genders. However, a small minority of interviewees considered the possibility of unconscious genderbias in the publishing system if the peer-review process is not anonymous.
Another suggestion was that the review process could be influenced because men and women canhave different writing styles—if men present their results in a more assertive way, it might give themmore credibility.

“

I don’t believe that the vast majority of men would be actively seeking to discriminate against
women. I do think it is an unconscious bias level the majority of the time. And that is to do with thelanguage that we use, and how emphatically men sell what they’re doing compared to women, andthe kinds of words that we use to describe what we’re doing, and why it’s important and the valuethat it has.”
Woman, UK, midlevel administrator : medicine & life sciences

PAGE 102 The Researcher Journey Through a Gender Lens

FIGURE 5.9

Representative quotes from interviewees on their perceptions of the
publishing system, categorized according to the different viewpoint
clusters and in relation to the two main parameters analyzed.
Gender balance is important

Open-minded men

Fair-minded men“Well, it’s not blind from the editor’s point of view. It’s blindfrom the peer reviewers. But if you talk about articles thatthe editor would knock off out of hand without even sending
it to peer review, it would be important to understand thenumbers there.”“I think there is no discrimination in these days. If results are
good, and publishable, they will be published.”

Discouraged womenAcademic system is biased“I have a friend, a colleague, that is very, very good in her
research [social sciences - terrorism]. And she is a woman
and she has had problems with these issues. She told methat in her area, women are also rejected. It’s more difficult
for them to publish and to get the citations.”

Fair-minded women“I want to say is that for the procedure to choose your papers
or the peer review will not be a biased choice, which paper toget [published]. For I was once an editor and I will not knowwhether the author is a woman or whether he is a man. So
that’s what I mean.”
Woman, China, assistant professor : medicine & life sciences

Academic system is fairMan, Australia, senior administrator : social sciences

Man, Greece, postdoctoral fellow : physical sciences

Woman, Spain, midlevel researcher : social sciences

Indifferent women
Aware men / women“The feeling that I got from speaking to women colleagues isthat they tended to be treated harsher in their criticism.”
Man, UK, research associate - physical sciences“And because it’s not anonymized, and I think it’s almost
impossible to anonymize it. So I’m not recommending that.
People start off with their prejudices, probably about thepeople they know or what they know about their work.”
Woman, Australia, professor : physical sciences“I haven’t had any bad experience in publishing, so I don’t
have any personal example to talk about this, because I
published several articles and I didn’t have any problem.”
Woman, Spain, midlevel researcher : social sciences

Indifferent men“[If women on average publish less, it is] because they are theminority in the research community. So it’s normal.”Man, Greece, postdoctoral fellow : physical sciences

Gender balance is not a high priority

Researcher Perspectives PAGE 103

There were also some possible explanations given for the difference in publishing between men
and women that were not related to the publishing system but rather to the academic context prior
to publishing, as mentioned in the previous section: women hesitating to believe they are ready for
publishing, not finding good collaborators, and less frequent conference attendance.

“

It might be because you kind of miss out on, scoring a really good collaborator, it might be because
you are not paid attention to as much in your lab and so your PI isn’t really pushing your researchalong. It may take you longer to publish, it may seem like you have to jump through more hoops
before you’re ready to publish.”
Woman, US, funding agency : medicine & life sciences““

There’s a hesitancy, sort of a almost psychological hesitancy of a lot of females to think that they’re
ready, to think that things are in good enough shape to be submitted for someone else’s review.”
Woman, US, funding agency : medicine & life sciences

So the fact that women are not as good at going to conferences as men, and that is also quite
well established. I think it’s they feel less inclined to leave home and family. So they don’t go toconferences, so they don’t meet people, so they don’t network as much. Then the referees don’tknow them. And even if it’s only a little difference every time, over a career it adds up.”
Woman, Australia, professor : chemistry

The majority of interviewees felt that there is no clear evidence or personal experience related to genderbias in citation. Some mentioned there are studies on this topic, but they were not directly confronted withthis issue themselves.
The funding system was not discussed to the same extent with all participants. There were interviewees
who believed the system to be fair and based on experience and on merit, while others perceived that thefunding system could be more susceptible to bias.

PAGE 104 The Researcher Journey Through a Gender Lens

““Funding does not depend on the gender, only or depends of your academic position. And so on.
And no dependence with gender.”Woman, Russia, associate professor : marine biology

When I was in the system, when I was a post-doc, when I was a grad student, I thought the system
was quite fair. Now that I’m working at what I would call an administrative systems level, looking
across and seeing all the data that we have as a funding agency—on the disproportionate rates offunding and on the disproportionate rates of publishing, gaining tenure, getting to mid-career
faculty—there’s no way I can still look at the system and think that it’s fair. I think it’s hidden.”
Woman, US, funding agency : medicine & life sciences

As for reasons given, the same factors affecting funding were mentioned by interviewees as were exploredearlier in this chapter:• More men researchers apply for grants than women researchers. Women may feel they are less readyto apply for a grant than men. Because funding proposals are usually not anonymous, there is thepossibility of unconscious bias from reviewers.
• Furthermore, with block funding, the university is responsible for distributing the grants, with aninternal board of senior administrators and researchers choosing who will be awarded funding. Thus,
the same gender bias issues that arise in the promotion process would apply to grant distribution.
Less funding can have a profoundly negative effect on academic careers, such that women researchers
cannot progress in their academic careers if they receive less funding. Without funding, they are unable tolead a group of researchers and productivity is lower, leading to fewer publications and a lower chance ofpromotion.

“

I think if a man gets more funding then they will finish more research and maybe they...are more
likely to get promoted. And then maybe [they would] have more students to do all their research forthem. Then the gap between a man and a woman gets bigger as time goes by.”Woman, China, assistant professor : medicine & life sciences

Researcher Perspectives PAGE 105

Sexual harassment
There is an extensive body of literature on
sexual harassment in academia and its negative
effects on the academic climate,59 researchers’
job satisfaction60 and health.61 In the openended section of the preliminary survey, many
women reported that sexual harassment has
impacted their scientific career in a negative way.
These responses were consistent with Elsevier’s
2019 active researcher survey, which found thatsexual harassment can be influential for women
researchers in terms of progressing in theiracademic careers. Specifically, significantly more
women than men felt that discrimination orharassment is a barrier to their career progression(Appendix C, Figure C.11), and significantly more
women than men contemplated leaving theircareer in research because they experienced
discrimination or harassment at work (Appendix C,
Figure C.5). Hence, the question of representationof women, especially at higher career levels, andharassment appear to be linked.

All interviewees agreed that sexual harassment
is a serious offense that should not be tolerated;
however, few of the interviewees had experienced
it directly. We were unsure if they were not awareof sexual harassment at their institution because
it did not exist or because it might not have beenreported (or kept from the public if reported). In
cases where sexual harassment was acknowledged,
universities were more likely to be actively
addressing it as a problem.

“

There’s been different surveys here, but if
you’re talking about even 20%, 30% or 40%
of females being harassed in the workplace,it's not acceptable.”
Woman, US, funding agency : medicine & life
sciences

To explore the perceptions of sexual harassment
and its impact on the research workforce, we
discussed the topic in our interviews.

59 Cortina, L. M., Swan, S., Fitzgerald, L. F., & Waldo, C. (1998). Sexual harassment and assault: chilling the climate for women in academia. Psychology of Women Quarterly, 22(3),419-441. doi: 10.1111/j.1471-6402.1998.tb00166.x
60 Chan, D. K. S., Tang, C. S. K., & Chan, W. (1999). Sexual harassment: a preliminary analysis of its effects on Hong Kong Chinese women in the workplace and academia. Psychologyof Women Quarterly, 23(4), 661-672. doi: 10.1111/j.1471-6402.1999.tb00390.x
61 Roosmalen, E. V. & McDaniel, S.A. (1999). Sexual harassment in academia: a hazard to women's health. Women & Health, 28(2), 33-54. doi: 10.1300/j013v28n02_03

PAGE 106 The Researcher Journey Through a Gender Lens

Some interviewees knew women who had experienced sexual harassment. According to them, women
researchers do not always report these experiences for various reasons:• Women sometimes consider this behavior “normal” in their culture;• In some cultures, women would feel too shy or embarrassed to report harassment;• Some women researchers said that if they expect no action to be taken in response to reportingharassment, they will not report it• Some women researchers are afraid of personal consequences for reporting harassment• In certain societies, men may consider it a compliment for a woman to be harassed“

And so then you have to work in an environment where people kind of know that you have reported
and they don't like that you have disturbed the peace and there can be, again, very low level, almost
implicit retaliation. Just a lack of opportunities given, lack of attention given, talking behind people’sback. There’s little kinds of things that are really important and really can affect one’s career. I thinkthat’s actually the bigger effect and I think that’s what keeping these women, some of whom are
my colleagues and I’ve heard this sort of thing directly, I think that’s what’s keeping them from
reporting. It’s not that it’s being handled badly up the top, but you then have to like live with theconsequences of the local level.”Man, US, assistant professor : clinical psychology

Some researchers recounted cases where harassment had been reported, but the university may
choose to “sweep the issue under the rug.” Sometimes the offender was reprimanded, but there were nofurther consequences (i.e., “they just got a slap on the wrist”). This was often the case if the harasser was aprofessor of high reputation who brings a large amount of research funding to the university or who theuniversity prioritizes to maintain its own reputation.

“

In terms of the US academic system, I think one of the reasons it seems to be tolerated is, ourschools...are heavily dependent on funding to stay afloat, far more so than tuition or any kind of
supplementation by the local government...What tends to happen is the ones who really get a freepass are university professors who are well established, they’re tenured and they bring in millionsof dollars a year to the university in research funding. It’s not in the university’s best interest to havethat research funding go away.”
Woman, US, funding agency : medicine & life sciences

Researcher Perspectives PAGE 107

Researcher Perspectives

Interventions Towards
Achieving Gender
Diversity and Equity:
Comments and Suggestions
Following our discussion with interviewees on their perceptions and personal experiences of gender
diversity and equity, we next asked about opinions on existing interventions and suggestions for futureinterventions towards achieving gender diversity and equity in academia.

Exploring the range of opinions on interventions
Through the open-ended survey questions, we collected responses on interventions that aim to achieve
gender diversity and equity in academia. During the interviews, we asked the researchers to commenton these interventions. The two main parameters we defined to categorize the perceptions towards
gender issues (importance of gender balance and perception of fairness of the system) aligned wellwith the respondents’ attitudes towards the interventions. These parameters also showed how different
interventions were favored by the different viewpoint clusters of the respondents, based on their attitudes
and personal experiences (Figure 5.10).

PAGE 108 The Researcher Journey Through a Gender Lens

FIGURE 5.10

Different attitudes toward interventions to achieve gender diversity
or equity, categorized according to the different viewpoint clusters
of interviewees, aligned along the two main parameters evaluated.
Gender balance is importantFair-minded men
Open-minded men / Discouraged women• Changing academic processes to avoid opportunity for(unconscious) bias
• Providing better childcare support for women and men• Changing culture by actively adding more women• Adding personal evaluation criteria that reward
collegiality and support roles• Creating more awareness on gender issues• Coaching/mentoring women to be more assertive andself confident• Providing better childcare support for women• Opening opportunities for women to work part time

Fair-minded women• Providing better childcare support for women and men• DISLIKE: Interventions that favor women because theirachievements are questioned

Academic system is fair

Academic system is biased• DISLIKE: being singled out as a role model

Aware men / women• Changing academic processes to avoid opportunity for(unconscious) bias
• Providing better chlidcare support for women

Indignant men• Aiming for interventions that support women, but arealso open to men who suffer same challenges (e.g.,childcare, lack of coaching etc.)

Indifferent men / women• No need for interventions to improve
gender balance/equity• DISLIKE: interventions that discriminate against men

Gender balance is not a high priority

Researcher Perspectives PAGE 109

The lack of consensus over a single best intervention may be interpreted as a lack of a “one size fits all”
intervention, as articulated by some of the interviewees:“

It’s understanding how best to target any intervention...because you’re dealing with men andwomen from many different backgrounds. What will work for women from one set of situations
doesn’t work for women in another set, so it’s hard to do something that will attract them all, andwork with them all.”
Woman, UK, professor, administrator : engineering, administrator role

The divergence in opinions regarding interventions could be summarized across three dimensions.
First, there were conflicting attitudes regarding whether interventions should “fix the women” or“fix the culture.” Both men and women felt that leadership training as an intervention could encourage
women to progress to more senior levels in their careers. The idea was that if women are taught to be
more assertive and less insecure, they will be better able to cope in the competitive environment toachieve more senior leadership positions. However, some researchers questioned whether this kind ofassertive culture should be the norm, on the ground that this kind of culture is not necessarily good for
either women or men in academia.

“

Why does that dynamic at that level have to operate at the level of being incredibly competitive? You
know, women might want to do those roles if the culture at that level was different, and that doesn’tmean that they will do those roles any less successfully. They might even do it more successfully andthat we should see the roles about what is being achieved, and not about being able to be cutthroat
enough to achieve it in a particular way.”
Woman, UK, midlevel administrator : medicine & life sciences

The second dimension of the opinions was whether interventions should take the form of quotas,
or that gender diversity will follow from interventions directed at the underlying causes and by raisingawareness.
One group of researchers (frustrated women and open-minded men) advocated for positive discrimination(quotas) as the only effective way to change the current culture in academia in the short term:“

To be blunt, I suppose the way you change that is by injecting a whole lot of women into the room.
If you’ve got a situation where you’ve got 1 woman and 20 men in a department, the way you changethat is by accrediting 10 women. And that will fundamentally change the culture of that department
over time. Are many of the men in that room going to enjoy that process? Probably not. But that’s
how you change it.”
Man, Australia, senior administrator : social sciences

PAGE 110 The Researcher Journey Through a Gender Lens

On the other side was a large group of interviewees who were strongly opposed to any sort of affirmative
action interventions that promote women in academia. Among women, the rationale was that women
want to be valued based on their achievements and not because of their gender. Men indicated thatit can be uncomfortable to experience being discriminated against through “unfair” promotion andencouragement of women. Additionally, it was suggested that these kind of interventions might be illegal
in some countries.

““

This is not something that I want. I don’t want to be seen as having to have a medal or a prize justbecause I’m a woman. It’s not a crutch that I need.”
Woman, UK, principal investigator : biology

No, [quotas would not be easily accepted in my organization]. I think men will have to change their
way of thinking. I guess men still feel uncomfortable with women or think women are not equal tomen. Even if you have the quota, women can still have disadvantages in doing the daily work. So
they can be excluded from meetings or not given the money for resources. For most other things,
which can not be put into any law. And harassment or mocking…such things can still happen even if
you force the quota.”
Man, Germany, postdoctoral fellow : medicine & life sciences

The third and last dimension that was suggested was whether interventions should be designed tosupport women only or whether they should also be open to men who suffer the same problems:“

I try to structure [interventions] for men and women that deal with the problems that women sufferfrom more than men suffer from. We have a fellowship that in practice has gone to women who've
been on maternity leave, but it is also open to men who've taken paternity leave as long as they've
had at least six months leave. So, as I say, in practice it has gone to women since it was instituted,
but men are eligible for it too, if they satisfy the eligibility criteria.”
Woman, Australia, professor : chemistry

Researcher Perspectives PAGE 111

Suggestions for future interventions by different
stakeholders in academia
During our interviews, we asked the interviewees to provide suggestions for interventions for achieving
gender diversity and equity in academia that they felt would be effective. We categorized their suggested
interventions based on the different levels of responsibility within academia: governments, universities,
funders and publishers. Below is a list of brief intervention suggestions given by the interviewees.

Suggestions for interventions at the government level:• Avoid gender bias and stereotypes in the early education system;• Promote women role models in science, specially STEM (science, technology, engineering andmathematics) fields;• Provide maternity support for women researchers

Suggestions for interventions at the university level:
The interviewees tended to think that as employers, universities are critically positioned to create genderbalanced environments. They noted different types of interventions targeting various systems at theuniversity level, but that all university interventions need to be a priority at higher levels of management.
Current interventions depend on initiatives by individual leaders, but broader strategies need to be
implemented at higher organizational levels in order to be successful and sustainable in the long term.

“

I think really it’s sort of a perfect moment. People, like executives at the top, really care about it.
At the same time that they’re doing a lot of networking events and sort of grassroots organization
within the university, some of which had been informal, some of them not, which has linked up
and over the last two years, I'd say sort of created a longer-term cultural shift. And it’s been driven
formally, but there’s an agenda equity strategy process. There’s also, I would say, a gender equity
self-assessment process, which is going on, which is to get formal bond accreditation in Australia.”
Man, Australia, senior administrator : social sciences

PAGE 112 The Researcher Journey Through a Gender Lens

Examples of recruitment interventions that were suggested:
•
•
•
•
•
•
•
•

Use more inclusive language in job posts;
Use transparent recruitment criteria;
Outsource recruitment to an external company to avoid nepotism;
When outsourcing recruitment to external agency, give instructions to provide a candidate list with asubstantial number of women;
Actively reach out to attract women candidates who may not be part of the current network;
Form mixed gender recruitment committees and take the time to understand the scientific role ofeach candidate;In cases of equal-quality candidates, recruit women;
Recruit based on quotas for ratios of men and women

Examples of promotion interventions that were suggested:• Use mixed recruitment panels and transparent evaluation criteria;• Evaluate candidates on more than just research output, for example, by giving credit for supporting
activities and collegiality (this approach is currently in place in Australia);• Take enough time for candidates to present themselves and discuss their role and contributions
Examples of mentoring and coaching interventions that were suggested:
Mentoring and coaching as an intervention to achieve gender diversity and equity was generally supported
by both men and women respondents. Some described that this type of mentoring is now mostly doneon an ad hoc basis, while it should be part of the institutional structure. Some of the respondents felt that
senior-level women or men who act as mentors or coaches can encourage women to:• Be noticed. Senior-level women can actively look for successful women who are standing in the
shadow of their PI or who are not actively promoting themselves;• Overcome their insecurities to publish, acquire grants or go for promotion sooner;• Hang in there when they need to overcome challenges, like rejections of grants or publications;• Learn from their shared stories on how they handled personal and professional issues, like childcare
or reacting to harassment or bullying“

I thought it was just me who had these experiences.”
Woman, China (from EU), lecturer : arts & humanities

Examples of work-life balance interventions that were suggested:
Some researchers reported having a positive working environment that supported them in balancing
a career in science with taking care of their children. Often this was dependent on the attitude of theirsupervisor rather than being an institutional norm. Recommended interventions were:• Allow flexible working hours to enable men and women to pick up children from day care or school;• Avoid scheduling early or late meetings during times when parents need to pick up or drop offchildren;• Provide childcare on campus to make it easier to pick up and drop off children and enable women tobreastfeed during working hours (e.g., this is common in Germany);• Offer the option to work part-time; though the researchers felt it would be good to have this asa personal choice, it was generally perceived that working part-time would delay a researcher’s
career progress.

Researcher Perspectives PAGE 113

Suggestions for interventions at the funder level:• Increase diversity in the senior leadership of funding agencies;• Anonymize peer-review of funding applications;• Require gender balance for large collaborative projects—make it necessary for project leaders toactively involve women researchers. One example of this are EU COST projects where bias is avoided
by making the funding applications are completely anonymized – the required information for allgroup members is only their field, their gender and their seniority level.
• Develop special awards for women and engage in outreach to make women aware of these funds andencourage them to apply;• Add a requirement that a university should have a gender-positive culture to receive funding; this will
create incentives for the entire institution to revise its culture. Obtaining, for example, Athena SWAN
status (bronze or silver) was often mentioned as a way to show that gender-related issues are being
addressed by an institution;• Add the possibility of explaining delays in career progression on a funding application, take into
consideration whether women (or men) researchers took time off to care for their children;• Offer additional funds to extend a project if a researcher gets pregnant and needs to extend project
deadlines;• Offer funds for women to go to conferences and help pay for additional childcare needed for themto attend

Suggestions for interventions at the publisher level:• Anonymize manuscript submission and use double blind peer-review to avoid bias;• Achieve gender balance among reviewers and editors;• Provide gender-related issues awareness training for peer-reviewers based on writing style (e.g. theperception that men are more assertive at presenting their results than women are) and language for
non-native authors“

The people who are leading those conversations, engaging in those conversations, developing
programming and interventions, they are the people who are kind of the least likely to need and tobenefit from those interventions and those conversations because they’re already committed to thecause…I think we really need to be thinking about how to engage everyone in discussions on thissort of thing. I think that there’s a lack of...I think people don’t know what they don’t know. And I
think that there’s a lack of awareness to these sorts of issues…It takes figuring out how to engage
equal, particularly the ones who don’t have some vested interest or just interest because they’reinterested. I think that that’s going to be the major contributor to moving the needle on this, andthat’s much harder to do than a major intervention.”Man, US, assistant professor : clinical psychology

PAGE 114 The Researcher Journey Through a Gender Lens

Expert Interview

Sandra W. Robert, CAE
Chief Executive Officer
Association for Women in Science (AWIS)How would you describe the current
state of gender diversity in research?
Are there initiatives, policies, orinterventions that have emerged in
the last 3-5 years that you feel have
impacted progress in gender diversity
in research and should be monitored?
I see that more people are talking about—andin a very open way—the gender bias that is often
brought to decisions regarding who is hired andwho is included in research. I was particularly
struck by the stance that the NIH director, Francis
Collins, took this summer against all-male speaker
panels, or “manels.” That was very significant. The
report from the National Academy of Sciences,
Engineering and Medicine, “Sexual Harassmentof Women: Climate, Culture, and Consequence inAcademic Science, Engineering, and Medicine,”
is referenced in almost every conversation I havein Washington, D.C. That report actually spurred
the formation of a scientific societies consortium
on sexual harassment, where more than 100
associations are now working together to develop
standards for addressing concerns around gender
equity and inclusion, as well as anti-harassment
policies. I think there is a lot more interconnection
taking place. People are not only paying attention
to gender disparity in research, they are now acting
on it in a systemic way.

What value do data and an evidencebase offer as tools to organizations such
as AWIS and the academies, as well as
policymakers, funders, and institutional
leaders to address issues of gender
diversity and equity?
The wonderful thing about data is that it helps
to neutralize conversations that could otherwise
be very pulled to one pole or another. Data helps
create a common platform for us to talk about
what is actually going on, and not make decisions
based on personal opinion. Data also gives us aplace to start the narrative—to understand what
is currently going on and what the gaps are.
Then we have the opportunity to identify the best

approaches and partners that will help us cross that
gap and move toward our desired future. Data isabsolutely essential for moving policy forward.

What information or insight fromthe report did you find particularlyinteresting, either from the perspectiveof AWIS or that of policymakers andinstitutional leaders?
I appreciate that this report combines both
qualitative and quantitative research; that is theapproach that AWIS takes toward research, and wefeel strongly that both types of data are extremely
important to a good analysis. Qualitative researchallows you to go deeper into the individual stories
and perceptions behind the quantitative data.
When we look at just the data, we’re left withmany questions. We might be able to see the fullscope and scale of a particular issue, but we need
qualitative data to make meaning of the numbers.
The visuals also clearly illustrate where we havebeen and where we are now in terms of gender
equity in research. I was particularly struck by
the gender differences in publication counts andthe publication histories of men and women
researchers, and the idea that the genderdifferences among authors may be related todifferences in invitations to collaborate.
The worldwide nature of the report is also
remarkable—not everyone has the means to do
this kind of broad study and it is important that
Elsevier is taking the initiative.

The trends identified in terms ofscientific publications are confirmed forboth awarded grants and even more
so when analyzing patents. From yourperspective, what do you think this says
about a gender innovation gap and theability to translate research?
I am personally very concerned about thepatent side of the equation. The US Patent
and Trademark Office report on trends andcharacteristics of US women in ventures, which

Expert Interview PAGE 115

It takes many different connection
points to create this kind of change
and we at AWIS appreciate the workthat Elsevier is doing.

came out in February 2019, is something that needs
more attention. AWIS and the National Women’s
Business Council have also been supporting newlegislation around more accurate tracking ofpatent data, particularly disaggregating data on
underrepresented groups so that we can better
understand the gaps and develop strategies toimprove participation in the patent process. We feelthat it is incredibly important to get a good read on
who is showing up and to track data in a way thatallows us to see the gaps and monitor change. My
colleagues in the US Patent and Trademark Office
are really keen on moving the needle on the issueof gender representation in innovation.

Thinking about the future of gender
diversity and equity in research globally,
within AWIS membership, within the
United States, or on a global scale,where do you think we will be in 10
years’ time and what do you thinkhave the most significant influence on
creating change?
I believe this is the first era in history that fivegenerations are working together. As the baby
boomer generation continues to retire, it will makemore space for new people, new voices, and new
perspectives to enter the research community. I see
that happening within our AWIS membership andwe celebrate it. As you know, we have a very strong
focus on furthering diversity and inclusion as key
considerations in innovation. This generational
shift in the research workforce will also be affectedby the expansion of new media channels thathave not been available previously. Platforms like
Twitter are allowing people to communicate about
their research and their perspectives in a personaland direct way. These platforms are giving a voice
to people who have been underrepresented inresearch, bringing down barriers and allowing
them to participate in the conversation and shape
the future direction of the research community.
These changes in the research workforce are
happening in a positive, healthy way and will
accelerate diversity and innovation.

PAGE 116 The Researcher Journey Through a Gender Lens

What impact, if any, has the #MeToomovement had in the world of research?
The #MeToo movement has greatly impacted oursociety at large. I think it has had a positive impact
and one that has been unanticipated in some ways.
There is a greater recognition of the need forcaution in terms of interactions in professional andsocial settings, but I’m not sure that has translated
into creating more balance and inclusion. But
we have to start somewhere. By bringing greater
realization about what has been going on andmaking it more public, the #MeToo movement
has had an overall positive impact. It has created a“call the heart” in which we can access the humanperspective and agree that this kind of inequality
and treatment of women cannot continue.

Are there any other thoughts you’d
like to share about the report or issues
related to gender diversity or equity inresearch?
As the CEO of AWIS, I respect Elsevier’s deep
commitment to continuing to study gender
diversity an equity and to be partners, not onlywith AWIS, but with the scientific community and
STEM professionals to address this issue in thelong-term. It takes many different connection
points to create this kind of change and we at AWIS
appreciate the work that Elsevier is doing. Women
have important things to share and they need to beable to show up and innovate.

Researcher Perspectives

Conclusion
The preliminary qualitative research survey andthe interviews demonstrate great diversity inperceptions and attitudes of gender in research.
We believe there is great value in recognizing thesedifferent perspectives, as this improves the chancesof finding effective solutions.
Classifying researchers by their attitude togender-related issues into eight viewpoint clusters
provides a deeper understanding of the diversityof opinions. Most of the differences in viewpoints
can be related to the importance that the individual
placed on gender balance and to the perceptionthat the academic system is fair.
When looking at most of the topics we discussedwith the interviewees, we see that on one hand,some clusters (men and women) tended toattribute gender inequality to the attitudes
and ambition levels of women. Other clusters
attributed gender inequality to a systemic andcultural (unconscious) bias against women. Evenin fields where the ratio of men and women isbalanced the proportion of women in more seniorlevels is reported to be lower than men.
We note consensus among interviewees thatfamily responsibilities can have a negative
impact on research careers (for both womenand involved men). In turn, the ambition levelof women is strongly influenced by challenges
women experience in combining family life
and a career. Many researchers reported thatwomen are expected to be the primary caregivers.
Women report a positive effect on their ability tosuccessfully advance in their career if they receive
childcare support (e.g., from their spouses, family,
external childcare provider).

The suggested interventions are in line with the
respondents’ different perceptions on the causesof gender-related issues. These interventions were
either aimed at increasing the assertiveness andself-confidence of women or at changing the maledominated culture and reducing implicit bias. Since
the differences in perceptions regarding effective
interventions were so large, we conclude that a
combination of multiple interventions is needed
rather than any single intervention or a one-sizefits-all solution.
Respondents to the survey who did provide open
answers that show they are indifferent men andwomen or indignant men did not agree to beinterviewed for this study. Consequently, we did
not discover viewpoints from men and women who
are indifferent to the gender discussion. Nor did
we speak to men who are negative about current
interventions that sometimes discriminate against
men. We feel that it will be important to uncover
their perceptions to understand how they can be
included in the discussions to create a diverse
research environment with equal opportunities forboth men and women.

AppendicesAppendix A

Methods and Experimental
Approach
Analysis of Bibliometric Data
DATA SOURCE:
The bibliometric data used for the analyses in this report were basedon the June 6, 2019 snapshot of the Scopus database.

if their second publication was published in or before 2005. We
included authors in the period 2014–2018 if their first Scopus-indexed
publication occurred in that period. We applied a two-publication
minimum filter to ensure that we were analyzing the active author
population and not those who publish only occasionally.

PUBLICATIONS INCLUDED IN THE ANALYSIS:CORRESPONDING AUTHORS, FIRST AUTHORSAND LAST AUTHORS:

Bibliometric analyses were based on three publication types
combined: articles, reviews and conference papers. Bibliometricindicators presented in this report, such as average number ofpublications and average field-weighted citation impact (FWCI), werebased on these publication types.

Authors in the positions of corresponding author, first author orlast author (as provided by the authors at the time of publication, as
captured in Scopus) were the subset of active authors who had everauthored a publication during the period of interest as corresponding
author, first author or last author, respectively.

AUTHOR DEFINITION AND DISAMBIGUATION(SCOPUS AUTHOR PROFILES):AUTHOR COUNTRY AND SUBJECT AREAASSIGNATION:

Data analyses were based on authors as listed on the author byline of
publications. Scopus uses a sophisticated author-matching algorithm
to precisely identify publications by the same author. The Scopus
Author Identifier assigns each author a unique ID (called the authorID) and groups together all documents published by that author intoa Scopus Author Profile, matching alternate spellings and variationsof the author’s last name and distinguishing between authors withthe same last name by differentiating on data elements associatedwith the publication (such as affiliation, subject area and co-authors).
The profile is enriched with manual, author-supplied feedback, both
directly through Scopus and via Scopus’ direct links with ORCID(Open Researcher & Contributor ID; https://orcid.org/). Gender is not
captured in Scopus Author Profiles.

We assigned authors to countries and subject areas based on their
publication output during the period of interest. Whole counting
methods were used for this process. Authors were assigned to a
country if more than 30% of their publications during the five-year
period of interest were from that country. Authors assigned to anyof the EU28 countries were also assigned to the category EU28. The
United Kingdom is included in the EU28, as was correct at time ofanalysis for the report. Similarly, an author was assigned to a subject
area if more than 30% of their publications during the five-year period
of interest were in that subject area. If an author did not meet thesethresholds for any country or any subject area, they were not assigned
to one.

AUTHORS INCLUDED IN THE ANALYSIS:
Authors included in the analysis were limited to those authors forwhom a first name could be determined (based on name data fromthe June 6, 2019 snapshot of Scopus, as described in the section “First
name determination”) and a gender could be predicted based on thelatest version of the NamSor API (i.e., surpassing a Gender Probability
Score of 1.735; described in the section “Gender Probability Score”).

ACTIVE AUTHORS:
Analyses of authors during the periods 1999–2003 and 2014–2018 werebased on “active authors.” We defined “active authors” as those having
published at least two publications (i.e., articles, reviews or conference
papers) during the period of interest. To ensure inclusion of earliest
career authors among those analyzed, we also included authors in the
period 1999–2003 if their first Scopus-indexed publication occurredin that period and they published at least one more publication
within five years of the first publication. For example, if an author’s
first publication was published in 2000, we included that author

SELECTION OF COUNTRIES TO INCLUDE IN THE
ANALYSIS:
To ensure that country-level analyses were based on robust data,
countries in the report were limited to those with at least 30,000
authors (enumerated based on the description in the section “Authors
included in the analysis”) with at least two publications during theperiod 2014–2018.
The prediction of gender based on name was dependent on two
factors: the author ID having a first name (as described in the section“First name determination”) and the Gender Probability Score
assigned to the author name by NamSor. We therefore included
additional thresholds to ensure that the prediction of gender based onname was similar across countries included in the report: countries
included in the report were limited to those for which at least 80%
of author profiles had a first name and at least 75% of author profiles
with a first name had a Gender Probability Score equal to or above
1.735 (described in the section “Gender Probability Score”).

Methods and Experimental Approach PAGE 119

SCOPUS ASJC MAJOR SUBJECT AREAS

BROAD CLUSTERSUBJECT AREA NAME USED IN THIS REPORT

Multidisciplinary (journals like Nature and Science)All

Publications in these journals are reclassified to the
26 subject areas listed below for this report

Agricultural and Biological Sciences

Life Sciences

Agricultural Sciences

Arts and Humanities

Social Sciences

Arts & Humanities

Biochemistry, Genetics and Molecular Biology

Life Sciences

BiochemistryBusiness, Management and Accounting

Social Sciences

Business

Chemical Engineering

Physical Sciences

Chemical Engineering

Chemistry

Physical Sciences

ChemistryComputer Science

Physical Sciences

Computer Science

Decision Sciences

Social Sciences

Decision Sciences

Dentistry

Health Sciences

Dentistry

Earth and Planetary Sciences

Physical Sciences

Earth & Planetary Sciences

Economics, Econometrics and FinanceSocial Sciences

Economics

EnergyPhysical Sciences

EnergyEngineering

Physical Sciences

Engineering

Environmental Science

Physical Sciences

Environmental Science

Health Professions

Health Sciences

Health Professions

Immunology and Microbiology

Life Sciences

Immunology

Materials Science

Physical Sciences

Materials Science

Mathematics

Physical Sciences

Mathematics

Medicine

Health Sciences

Medicine

Neuroscience

Life Sciences

Neuroscience

Nursing

Health Sciences

NursingPharmacology, Toxicology and Pharmaceutics

Life Sciences

Pharmacology

Physics and Astronomy

Physical Sciences

Physics & Astronomy

Psychology

Social Sciences

Psychology

Social Sciences

Social Sciences

Social Sciences

Veterinary

Health Sciences

Veterinary

PAGE 120 The Researcher Journey Through a Gender Lens

SUBJECT AREAS AND SUBFIELDS INCLUDED IN
THE ANALYSIS:
Titles in Scopus are classified under four broad subject clusters (lifesciences, physical sciences, health sciences and social sciences &humanities), which are further divided into 27 major subject areas(known as All Science Journal Classification or ASJC). Titles may
belong to more than one subject area. Subject areas in this report are
based on 26 subject areas, with titles classified as “Multidisciplinary”
by ASJC reclassified for this report.
To define subfields of research within medicine, we leverageda system in which the major subfields of medicine are further
classified into subcategories. Because there is considerable overlap insome subcategories, we defined medicine subfields by grouping theappropriate subcategories based on the frequency that publications
were categorized in overlapping subcategories. For example, wecreated the subfield “Fertility & Birth” because a high percentage of
publications in the subcategory “Obstetrics and Gynecology” werealso classified in the subcategory “Reproductive Medicine”. Further,for inclusion in this analysis, we focused on subcategories with lessthan 40% overlap in the author population compared with the major
subject area of medicine. That is, if more than 40% of authors froma subcategory or subfield were also represented in the major subject
area of medicine, we considered the two populations of authors tobe sufficiently similar that analysis of the subfield would not yield
major insights. The final selection of research subfields in medicine
is shown here.

MEDICINE SUBFIELD NAMESUBCATEGORIES INCLUDED

CancerCancer ResearchOncology

Cardiology & Pulmonology

Cardiology and Cardiovascular Medicine
Pulmonary and Respiratory Medicine

Diabetes & Endocrinology

Endocrinology
Endocrinology, Diabetes and Metabolism

Emergency Medicine

Critical Care and Intensive Care Medicine
Emergency Medicine

Fertility & Birth

Obstetrics and Gynecology
Reproductive Medicine

General Clinical Medicine

General Medicine
Family PracticeInternal Medicine

Infectious Diseases & Allergy

Immunology and Allergy
Infectious Diseases
Microbiology (medical)

Pediatrics

Pediatrics, Perinatology and Child HealthPublic Health

Epidemiology
Health Policy
Public Health, Environmental and Occupational HealthRadiology & Imaging

Radiology, Nuclear Medicine and Imaging

Surgery

Surgery

We also explored whether the following subfields would provide additional insight. However, we found that more than 40% of authors fromthese subfields (defined according to the subcategories listed) were also represented in the major subject area and therefore would not provide
more insight than what was provided at the subject area level.

MEDICINE SUBFIELD NAMESUBCATEGORIES INCLUDED

MAJOR SUBJECT AREA

Infectious Diseases & Allergy

Immunology and Allergy
Infectious Diseases
Microbiology (medical)

Immunology &Microbiology

Neurology

Neurology (clinical)
Neurology

Neuroscience

Methods and Experimental Approach PAGE 121

The following subfields were assessed but were not presented because results were similar to the subject area of biochemistry.

MEDICINE SUBFIELD NAMESUBCATEGORIES INCLUDED

Biochemistry & Biophysics

Biochemistry
Biophysics
Structural Biology

Biotechnology

Biotechnology
Applied Microbiology and Biotechnology

AUTHOR GENDER INFERENCE:
We used NamSor to infer the gender of authors. NamSor treatsgender as a binary variable and is only able to infer the gender as“woman” or “man.” We acknowledge that this poses a limitation to
fully assessing gender inclusiveness.
A binary gender was inferred for author IDs using the NamSor API(January 2019 release). The API provides a Gender Probability Score
and gender classification based on three data points: country oforigin, first name and last name. We generated these three data
points for authors based on information related to each author ID.

Determination of author country of origin:
We determined each author’s country of origin based on the countryof affiliation listed on the publications from their first year of
publication in Scopus (i.e., articles, reviews and conference papers). In
some cases, authors had published in more than one country in theirfirst year of publication. In these cases, we designated the country
with the largest number of publications as the author’s country oforigin. Authors with equal numbers of publications in two or morecountries were excluded from the gender disambiguation analysis.
The process used to determine the author country of origin issummarized here.
For each author ID:
1. Identify year of first publication in Scopus.
2. Identify all publications from the first year that the author
published.
3. Identify the country affiliation indicated by the author in theirfirst-year publications.
4. Tabulate the countries of affiliation.
5. Tabulate the number of times each country was listed as thecountry of affiliation in the first year of publication.
6. Assign the author ID to the country most often indicated as thecountry of affiliation in the first year of publication as the countryof origin.
7. If two countries appeared as the country of affiliation for an
author an equal number of times in the first year of publication,then that author was excluded from the analysis.

First name determination:
First and last name are required as input data for NamSor. Therefore,
only author IDs with a first and last name were passed through the
NamSor API to retrieve a Gender Probability Score. All author IDs forwhom no first name data was available were not included in
the analysis.

PAGE 122 The Researcher Journey Through a Gender Lens

Different variants of an author’s name are commonly observed acrosstheir publications. To identify the best first name to pass through
NamSor for each author, we assessed all the name variants associatedwith each author ID. For each author ID in the Scopus snapshot,
we examined all publications on which the author ID appears in theauthor field and generated a list of all distinct first names associatedwith the author ID. Based on this list, we generated a table with arevised first name for each author ID. The process used to determine
the best first name to pass through NamSor is described here.
In cases where only a single first name was associated with anauthor ID:
1. When the name was of zero length, the best first name was
assigned as nulle.g., author first names: [ ]best first name: null
These author IDs were excluded from the analysis.
2. When the name was not of zero length, we removed thefollowing nonsensical characters if they were leading or trailing:“-!#&”
e.g., author first names: [“Tom&”]
best first name: TomIn cases where multiple first names were associated with an author
ID, we selected the longest available name following removal of
nonsensical characters, provided this name was not composed of astring of initials, according to the following steps for each author ID:
1. Author first names were collected into a list.
2. Author first names were initialized as the empty string ‘ ’.
3. The list of names was looped through. Each name in the list was
stripped of nonsensical leading and trailing characters (-!#&).
4. The next name in the list was considered and subjected to thesame treatment. If the length of the string was longer andnot composed of a string of initials, this next name was thenassigned as the revised first name. We identified a string of
initials among author first names by comparing the number of
periods that appear in the string to the number of characters(excluding whitespace, periods and nonsensical characters).
When the number of periods was equal to the number ofcharacters, this string was identified as a string of initials. Thiswas done using Regex expressions.
5. This process was repeated until the end of the list of author firstnames is reached.
e.g., author first names: [“Samantha”, “#Sam”, “Sam”, “S. E.”]
best first name: Samanthae.g., author first names: [“Samuel”, “#Sam”, “Sam”, “S. E.”]
best first name: SamuelGender Probability Score:

AUTHOR PUBLICATION HISTORY:The NamSor Gender Probability Score was used to predict the genderof each author. The Gender Probability Score is the natural log of theratio of probabilities, as determined by a Naïve-Bayes model, of thename receiving the classification of either MALE or FEMALE. The
Gender Probability Score is based on the best first name, last nameand country of origin.

Author publication history was determined based on the year in which
the author’s first publication appears in Scopus. We binned authors
into groups based on the year of their first publication as follows:

To predict the gender of each author, we first created a tablecontaining unique name-country combinations (represented in the
Scopus snapshot) from the following three fields:• best first name (based on the process described in the section“First name determination”)• last name (based on author ID)• country of origin (based on the process described in the section“Determination of author country of origin”)
We next took the resulting name-country combinations and passed
them through the NamSor API, which generated a classification(either MALE or FEMALE) with the associated Gender Probability
Score for each combination.
The detailed equation for the following classification and Gender
Probability Score are:Gender Probability Score (MALE) = ln

Gender Probability Score (FEMALE) = ln

Prob(MALE)
Prob(FEMALE)
Prob(FEMALE)• Group A – first publication in Scopus in 2003 or earlier (but not
before 1930)• Group B – first publication in Scopus between 2004 and 2008
• Group C – first publication in Scopus between 2009 and 2013
• Group D – first publication in Scopus between 2014 and 2018.

HYPER-AUTHORED PUBLICATIONS:
Author count varies across subject areas, with some subject areas
accounting for a greater proportion of hyper-authored publications.
We assessed whether it was reasonable to define hyper-authoredpublications for each subject area as those publications with an author
count greater than the author count for the majority of publicationsin the same ASJC (All Science Journal Classification) subject area.
We considered using an author count of 1.5 times the interquartile
range for authors in that subject area as a reasonable threshold for
defining and excluding hyper-authored publications; however, wefound that using this threshold would result in exclusion of a large
number of publications. For example, in the subject area of medicine,
excluding publications with an author count higher than 1.5 times theinterquartile range would result in the exclusion of any publications
with more than six authors. In the absence of a standardized method
to set the threshold of author count to define hyper-authoredpublications, we decided to include hyper-authored publications in all
analyses of bibliometric measures in the report.

Prob(MALE)

We set a threshold value for Prob(CLASSIFICATION) by testing
against a dataset of 2,260 athletes competing in the 2012 Olympics
in London. The dataset included each individual’s first name, last
name, self-identified gender and country. The Prob(CLASSIFICATION)
threshold of ≥0.85 on the Olympics dataset corresponded to recall
and precision rates of 98.0% / 93.0% for men and 87.8% / 98.3% forwomen, resulting in an F1 score of 0.95 for men and 0.93 for women.
Due to the high F1 score, we used the threshold of ≥0.85 (equivalent
to Gender Probability Score ≥1.735) to infer gender.
Once the Classification and Gender Probability Score wereobtained for each name-country combination, we solved forProb(CLASSIFICATION). Gender was assigned for name-country
combinations that had Prob(CLASSIFICATION) ≥0.85. Name-country
combinations that fell short of this threshold were classified as
UNKNOWN. The gender inferred for each name-country combination
was then matched to author IDs based on the best first name, last
name and country of origin.

Methods and Experimental Approach PAGE 123

AVERAGE NUMBER OF PUBLICATIONS:
The average number of publications by men and women was calculated as the arithmetic mean of the number of publications
by each active author during the period of interest and within a given group (based on gender, country and subject area).
For example, the average number of publications authored by women who were active authors in Argentina in the field of
medicine during the period 2014–2018 was 3.2 publications. This value is the arithmetic mean of the publication count of
the 9,938 women who were active authors in medicine in Argentina during the period 2014–2018. Author assignation to a
country, subject area and period were determined as described in the section “Author country and subject area assignation.”
All publications by an author, once assigned to a country, subject area and period, contributed to that author’s publication
count. Publications were counted using whole counting rather than fractional counting. For example, a publication listing
five authors in the author byline counted as a single publication towards the publication count of each author, rather thancontributing 0.2 publications towards each author’s publication count.
We determined the average number of publications by men and women among authors in the position of corresponding
author, first author and last author using the same approach, except that the calculation was based only on those authors
who had ever published as corresponding author, first author or last author, respectively. We limited the calculation of
publications in which the author was first or last author to those publications that did not have authors listed in alphabeticalorder and that had at least three authors.
The example illustrates how average publication count was calculated for a hypothetical group of active authors of the samegender in a given country and subject area. The number of publications for each author A, B, C and D is given in the table,with the average number of publications for the authors in each author position provided in the bottom row.

AUTHOR POSITIONAUTHOR

ALL

CORRESPONDING

FIRST AUTHORLAST AUTHOR

A

9

4

1

1

B

10

7

3

1

C

11

n/a

n/a

n/a

D

6

4

n/a

1

Average

9

5

2

1

n/a indicates the author had no publications in this position.

PAGE 124 The Researcher Journey Through a Gender Lens

AVERAGE FIELD-WEIGHTED CITATION IMPACT(FWCI):
Field-weighted citation impact (FWCI) is an indicator of the academic
impact or reach of a publication. It is calculated by comparing thenumber of citations actually received by a publication with the numberof citations expected for a publication of the same type, publication
year and subject area. An FWCI of more than 1.0 indicates that the
publication has been cited more than would be expected based on the
global average for similar publications. For example, an FWCI of 2.1
means that the publication has been cited 110% more than the world
average for similar publications. An FWCI of less than 1.0 indicatesthat the publication has been cited less than would be expected basedon the global average for similar publications. For example, an FWCI
of 0.9 means that the publication has been cited 10% less than theworld average for similar publications.
In general, the FWCI is defined as:
FWCI=

Ci
Ei

with
Ci = citations received by publication i
Ei = expected number of citations received by all similar publicationsin the publication year plus the following three years
When a publication was allocated to more than one subject area, theharmonic mean was used to calculate FWCI.
To calculate the average FWCI among men and women, we first
calculated the arithmetic mean FWCI for each author based on their
publications during the period of interest. This was done using
fractional counting and a weighted average. For a publication with
N authors, each author on that publication was assigned a fractionalcount of 1/N. In order to calculate an author’s FWCI over their body ofwork, the author’s fractional count for each publication was multipliedby the publication’s FWCI. These products were then summed anddivided by the sum of the of all fractional counts assigned to theauthor.

AUTHORSHIP CONTINUITY OVER TIME:
Author continuity studies were based on two cohorts of authors:
one cohort that first published in 2009 and a second cohort that firstpublished in 1999. Authors in these cohorts were assigned to a country
and subject area based on their publications in the five-year periodsof 2009–2013 or 1999–2003, respectively. An author was assigned
to a country if more than 30% of their publications in the five-year
period of interest listed an affiliation based in that country. Similarly,
an author was assigned to a subject area if more than 30% of their
publications in the five-year period of interest were in that subject
area. These assignations were based on whole counting methods.
As part of the analysis, for each author in the two cohorts, we
determined the year of the last publication indexed in Scopus anddefined the time span between the first and last publication as theperiod during which they authored papers.

AUTHOR MOBILITY:
Author mobility studies were based on two cohorts of authors: one
cohort that first published during the period 1999–2003 and a second
cohort that first published during the period 2003–2013. We defined anauthor’s country of origin as described in the section “Determinationof author country of origin.” Authors with a null country in their firstpublication (i.e., no country associated with the author affiliation listed
or no affiliation listed) were excluded from the analysis.
To assess author mobility, we categorized authors as those who neverpublished with an affiliation outside their country of origin and those
who published with an affiliation outside their country of origin
at least once between the time of their first publication and 2018.
Authors with only one publication were not included.
Bibliometric analysis of author mobility within each cohort was
based on publications by authors from each cohort during the period
2014–2018. The average number of publications and average FWCI
were calculated as described in the sections “Average number ofpublications” and “Average Field-weighted Citation Impact (FWCI).”We also calculated the arithmetic mean FWCI for each author basedon their publications as corresponding author, first author and lastauthor. These calculations were done using the same method of
fractional counting and a weighted average, with the exception thatthe corpus of publications was restricted to those publications forwhich the author was the corresponding author, first author or lastauthor, respectively. Publications in which authors were listed inalphabetical order and those with two or fewer authors were excluded
from the calculations related to first and last author.
The average FWCI among men and women in a country and subject
area was calculated by taking the arithmetic mean of the FWCI for
authors in the group.

Methods and Experimental Approach PAGE 125

AUTHOR COLLABORATION NETWORK ANALYSIS:Network specifications:
Author collaboration network analyses were based on a defined set of
focal authors and their collaborators. Focal authors were defined as
those authors who:
•
•
•
•
•

Were deemed “active authors”
Published in the year 2013
First published in or after 1989
Had a first name associated with their Author ID
Had a gender predicted using NamSor

Active authors were defined using the approach described in thesection “Active authors.” Authors were deemed active if they publishedat least two publications (i.e., articles, reviews and/or conference
papers) during the period 2009–2013. Additionally, authors whose
first Scopus-indexed publication occurred in 2009–2013 who thenpublished at least one publication within five years of the firstpublication were also included so that earliest career authors would
be represented among the focal author set. We excluded authors
who published before 1989 from the focal set to ensure that we could
disaggregate authors by year of first publication and still work with arobust number of women and men among authors. 87% of authors
who published in 2013 first published in or after 1989. Author’s firstname and gender were determined as described in the section“Authors included in the analysis.” Author first name determinationand gender inference was done as described in the section “Author
gender inference.”
Collaborative network profiles were built for focal authors based on
their co-authorships (i.e., publications with other authors) during thefive-year period, 2009–2013. We selected this period for analysis topermit assessment of future outcomes (i.e., in the period 2014–2018)of the cohort. We built an author-level collaboration network where
the “nodes” in the network represent authors and the connections
between them (i.e., the “links”) represent co-authorship relationships,
defined as instances where the authors connected by the links
appeared together in one or more papers during the five-year period.
We used a five-year network window to capture ongoing and repeatedco-authorship ties, with the understanding that this approach would
capture network and productivity statistics bounded in time and notnecessarily characteristic of an author’s full set of co-authors andcollaborative activities across their career.
To retain network integrity, all focal authors and their co-authors
on publications during the period 2009–2013, regardless of theirproductivity during the period, inferred gender or assigned country/
region and subject area, were included to generate collaboration
network characteristics.

PAGE 126 The Researcher Journey Through a Gender Lens

We assessed whether hyper-authored publications should be includedin the analysis. Participation in hyper-authored papers can have adramatic impact on connectivity of authors within collaboration
networks. Therefore, we also assessed whether men and womenare differentially represented in hyper-collaborative research. As
only small differences between men and women were observed inaggregate (with men slightly more likely to be represented on hyperauthored papers in some subject areas and countries/regions), we
included these publications in this analysis as they appeared to havelittle influence on the trends.
For each focal author analyzed, we computed the following measures(see also):• Network centrality: the number of direct collaborators, i.e., thenumber of unique authors with whom the focal author coauthored papers with during the five-year time period• Second-order collaborators: the average number of collaboratorsof an author’s direct collaborators, i.e., the average number ofcollaboration ties of the direct collaborators of a focal author• Direct collaborators’ gender composition: share of direct
collaborators by gender• International reach: share of direct collaborators who were notassigned to the same country and/or region as the focal author.
Note that the EU28 region was treated as a single geographic
area, meaning that international collaborators of authors
assigned to the EU28 were defined as those authors assigned tocountries outside the EU28
• Direct collaborators’ publication history: average number ofyears from the year of first publication until 2013 of focal authors’
direct collaborators

To measure the network gender composition and international reachof focal authors, we classified the focal authors’ direct collaborators by:• Gender• Country/region similarity compared to focal author
Gender was determined and country/region and subject area wereassigned to direct collaborators as described in the sections “Author
gender inference” and “Author country and subject area assignation,”
respectively.
The collaboration network among all authors who publishedbetween 2009 and 2013 comprised 144,347,507 links (co-authoredpublications) and 10,470,713 nodes (authors). Although we utilized
the full network (all years [2009–2013], subject areas and countries)
to generate network statistics, we focused on 16 region-subject
pairs. These region-subject pairs are defined based on focal author
assignation to 16 combinations of regions and subject areas selectedof analysis. The regions selected for analysis were Brazil, Japan,
USA and EU28 and the subject areas selected for analysis were
biochemistry, business & economics, engineering and medicine.

FIGURE A.1

Toy networks depicting two hypothetical focal
authors within networks that have different structuralcharacteristics. A) I focal author (black circle) is tied
to two direct co-authors (red and blue circles), which
are in turn connected to five co-authors (gray circles,
second-order collaborators of the focal author). This
results in a direct network centrality equal to 2 andan average number of second-order collaborators
equal to 5. B) The focal author (black circle) is tied toeight direct co-authors (red and blue circles), which
are in turn each connected to a single co-author(gray circles, second-order collaborators of the focal
author). This results in a direct network centrality
equal to 8 and an average number of second-ordercollaborators equal to 1. For the analyses in thisreport, each direct co-author was assessed basedon inferred gender and assigned country/region,
represented here as different node colors, to compute
the gender composition and international reach of
direct co-authors.

The subject area of business & economics was created by combining
two major subject areas: “Business, Management and Accounting”
and “Economics, Econometrics and Finance”. We combined thesecategories because we observed high (i.e., greater than 40% in somecases) representation of authors in both subject areas. For example,
76% of the authors in the subcategory of accounting (within Business,
Management and Accounting) were also represented in finance(within Economics, Econometrics and Finance). Furthermore, our2017 analysis revealed that both subject areas had similar ratios ofwomen to men.
The final sample size of the focal author set (i.e., authors who wereassigned to the 16 region-subject pairs studied in this report) was
1,271,488. Of these, 875,492 were men and 395,996 were women.
The EU28 contained the greatest number of focal authors (661,911),
followed by USA (445,046 authors), Japan (128,277) and Brazil (54,064).
Medicine had the greatest number of authors in the focal set (728,143),
followed by biochemistry (459,195), engineering (324,025) and business& economics (53,801).

A

B

Methods and Experimental Approach PAGE 127

Stratification of authors by their first year of publication:
We stratified authors into groups based on the year that their first publication appears in Scopus to ensure that we were comparing authors
with similar publication histories as follows: 2009–2013, 2004–2008, 1999–2003, 1994–1998 and 1989–1993. For more details on distribution ofobservations by author groups, see Table A.1.

TABLE A.1

Number of observations within each subject area, country/region,
gender and year of first publication within each network analyzed.

SUBJECT AREAGEOGRAPHY

GENDER

Women

EU28

Men

Women

USA

Men

PAGE 128 The Researcher Journey Through a Gender Lens

YEAR OF FIRSTPUBLICATIONMEDICINE

BIOCHEMISTRY

ENGINEERING

BUSINESS &ECONOMICS

2009–2013

100,426

65,07922,262

6,866

2004–2008

21,572

14,566

4,197

1,318

1999–2003

14,172

9,398

2,477

684

1994–1998

9,353

6,559

1,347

290

1989–1993

6,161

4,206

737

132

2009–2013

95,18058,88584,50912,821

2004–2008

30,563

18,347

19,8493,471

1999–2003

25,306

14,406

13,7592,420

1994–1998

20,683

12,167

8,954

1,387

1989–1993

17,345

9,327

5,907

847

2009–2013

57,32832,532

8,889

2,814

2004–2008

12,278

7,327

1,469

649

1999–2003

7,987

4,390

892

483

1994–1998

5,614

3,099

561

302

1989–1993

3,934

2,095

359

192

2009–2013

80,35758,781

52,2537,127

2004–2008

23,12418,012

11,0272,015

1999–2003

17,496

11,914

7,501

1,759

1994–1998

13,540

9,010

5,632

1,338

1989–1993

11,214

6,918

4,532

1,029

SUBJECT AREAGEOGRAPHY

GENDER

Women

Japan

Men

Women

BrazilMen

YEAR OF FIRSTPUBLICATIONMEDICINE

BIOCHEMISTRY

ENGINEERING

BUSINESS &ECONOMICS

2009–2013

7,431

5,185

1,608

108

2004–2008

1,223

907

219

16

1999–2003

701

532

152

10

1994–1998

465

311

80

6

1989–1993

294

200

40

4

2009–2013

28,262

18,68922,237613

2004–2008

8,508

5,774

4,801

172

1999–2003

6,796

4,655

3,988

100

1994–1998

5,493

3,563

2,934

56

1989–1993

4,460

2,665

2,298

52

2009–2013

11,911

6,456

1,835

447

2004–2008

1,986

1,097

283

28

1999–2003

1,177

623

147

19

1994–1998

693

380

80

11

1989–1993

379

219

29

1

2009–2013

10,956

5,774

5,945

1,097

2004–2008

2,193

1,159

1,173

149

1999–2003

1,379

699

881

66

1994–1998

912

450

461

21

1989–1993

608

281

234

12

Methods and Experimental Approach PAGE 129

Network and metrics definition:

AWARDEES INCLUDED IN THE ANALYSIS:We defined A=[a_ij] as the adjacency matrix describing theconnections among all the authors (nodes) in the network, such thatthe entry a_ij is equal to 1 if there is a link (collaboration) from i to j,
and zero otherwise.

Awardees included in the report were limited to those for whoma Scopus author ID was available and the associated Scopus
author ID data (first name, last name and country of origin) could
support gender inference (as described in the section “Analysis of
Bibliometric Data”). Awardee names in the Elsevier’s funding databasewere matched to Scopus author IDs based on awardee name andinstitution details.

Thus, the count of direct collaborators of an author i, or equivalently
its degree d_i , in the network of collaboration was defined as follows:
di =FUNDING AGENCIES INCLUDED IN THE
ANALYSIS:

∑a

ij

j

The average number of second-order collaborators was computed
as the average degree of an author i’s direct collaborators j and was
defined as follows:
di =

∑d

i
j

<d >=
i
j

j

All agencies indexed in the Elsevier funding database that granted a
research award with a start date during the time period 2014–2018
to an individual with an author ID were included in the analysis andcontributed to the country-level statistics.

AWARDEE COUNTRY ASSIGNATION:

with d_j^i being the degree of i’s direct collaborators and d_i thenumber of direct collaborations.

We assigned awardees to countries based on the country that thefunding agency awarding the grant is located. Awardees who received
grants from more than one funding agency based in more than one
country thus counted towards more than one country or region.

Analysis of funding data

SELECTION OF COUNTRIES TO INCLUDE IN THE
ANALYSIS:DATA SOURCE:

Awardees were aggregated at the country level based on the countryof the awarding funding agency. Therefore, awardees were assigned toa country based on the location of the funding agency. To ensure wewere working with a robust data set, we limited the analyses to thosecountries with at least 5,000 awardees (enumerated based on thedescription in the section “Awardees included in the analysis”) during
the period 2014–2018.

di

The funding data used for the analyses in this report were based ona snapshot of the Elsevier’s funding database, taken June 9, 2019.
This snapshot was chosen as it is the closest in time to the Scopus
snapshot used for the bibliometrics analyses (June 6, 2019).

AWARDS INCLUDED IN THE ANALYSIS:
Analyses of grants were limited to research awards with start dates
between 2014 and 2018, inclusive. Awards coded as “research awards”
in the database were defined as those that support discrete, specified,researcher-initiated projects to be performed by named investigatorsin areas representing their specific interest and competencies. The
following phrases in the synopsis or description and abstract sections
were used to identify research awards:
•
•
•
•
•

Support or assist (some type of research)
Foster or encourage research
Enhance current research
Offer funds to support or encourage research
Grant support for investigators

Consistent with our approach for selecting countries for bibliometricanalyses (as described in the section “Analysis of Bibliometric Data),
we limited the countries included in the analysis of grants andawardees to those countries for which at least 80% of author profiles
had a first name and at least 75% of author profiles with a first name(as described in the section “First name determination”) had a Gender
Probability Score equal to or above 1.735 (described in the section“Gender Probability Score”). Among those countries that passed thesethresholds, the percentage of awardees for whom gender could not be
inferred represented less than 1% of awardees.

AWARDEE GENDER INFERENCE:
Awardees were matched to their Scopus author ID and gender wasinferred as described in the section “Author gender inference.”

AVERAGE NUMBER OF AWARDS:
The average number of awards granted to men and women was
calculated as the arithmetic mean of the number of awards received
by each awardee during the period of interest and within a given
group (based on inferred gender and assigned country). Awards werecounted using whole counting rather than fractional counting. For
example, an award listing four awardees as recipients counted as asingle award towards the award count of each awardee, rather thancontributing 0.25 awards towards each awardee’s award count.

PAGE 130 The Researcher Journey Through a Gender Lens

Analysis of patent data

INVENTORS INCLUDED IN THE ANALYSIS:DATA SOURCE:

Inventors included in this analysis were limited to those who
appear as inventors in any patent application filed with USPTO or
EPO, regardless of if the patent was granted or not, during two
periods based on the filling year at the patent office: 1999–2003 and2012–2016. We assessed patents in 2012–2016 rather than 2014–2018
as in the bibliometric analyses because patent applications must be
published before they appear in PATSTAT, which results in a lag of up
to 18 months for patent offices such as the EPO.

The data used for the analyses of patent applicants and inventors inthis report were from the 2019 Spring Edition of PATSTAT, a patent
database covering close to 100 patent authorities worldwide.

PATENT AUTHORITIES INCLUDED IN THE
ANALYSIS:
Inclusion of patent offices in the analysis was based on the quality ofdata provided by each patent office. We evaluated data quality for theIP5 offices (the 5 offices covering the largest markets) as follows:• United States Patent and Trademark Office (USPTO) data
were included because 98% of patents include the names of
the inventors and 98% of patents include the country of theinventors. One caveat is that applicants on USPTO patents may
ask that their application not be published until the patent isgranted. Therefore, USPTO patent data included in this reportwere for inventors and applicants with applications that havealready been published.
• European Patent Office (EPO) data were included because 95%of patents include the names of inventors and 95% of patents
include the country of the inventors.
• China National Intellectual Property Administration (CNIPA) data
were excluded because although the names of the inventors arereported for 95% of all applications, the country of the inventor
is reported for only 14% of all applications; thus, we were unable
to assign inventors to countries.
• Japan Patent Office (JIPO) data were excluded because
although the names of the inventors are reported for 85% of
all applications, the country of the inventors is reported forless than 1% of all applications; thus, we were unable to assign
inventors to countries.
• Korean Patent Office (KIPO) data were excluded because
although the names of the inventors are reported for 92% of all
applications, the country of the inventors is reported for only 75%
of all applications; thus, we were unable to assign inventors tocountries. Although these values were relatively high, we elected
not to include KIPO data because inventor gender inference
as described in the section “Analysis of Bibliometric Data,” wasexpected to return a low level of precision and recall based on
the high number of inventors from Korea (approximately 75% of
inventors with country information were from Korea).

INVENTOR AND ASSIGNEE DEFINITION AND
DISAMBIGUATION:
Data analyses were based on inventors, defined as those named as
inventors on the patent (those who contribute to the claims of apatentable invention), and assignees (the subset of inventors who own
intellectual property rights to patents), defined as those named as
assignees on the patent.
To determine if two inventors or assignees of the same name were
the same person, we used the unique identifier, doc_std_name_id
key found in table tls206_person in PATSTAT. This key is similar to theauthor ID in Scopus in that it aims to group all person_name data
related to the same individual under a single key.

ASSIGNEES INCLUDED IN THE ANALYSIS:Assignees are the subset of inventors who own intellectual property
rights to patents and are listed as patent assignee on a given patent.
For the majority of patents, patent assignees were corporations, but
in some cases, some or all the inventors also owned the IP rights andwere thus were named as both inventors and assignees. Assignees
included in this analysis were limited to those who appear as assignee
in any patent application filed with USPTO or EPO, regardless of if
the patent was granted or not, during two periods: 1999–2003 and2012–2016, based on the filing year at the patent office.

INVENTOR COUNTRY ASSIGNATION:
Inventors were assigned to a country if at least 30% of their patentapplications during the period of interest indicated that country as theinventor country. Therefore, inventors could be assigned to more than
one country within a period if the share of patent applications washigher than 30% for more than one country.

ASSIGNEE COUNTRY DETERMINATION:
Assignees were designated to a country if at least 30% of their patentapplications during the period of interest indicated that country as
the assignee country. Therefore, assignees could be assigned to morethan one country within a period if the share of patent applications
was higher than 30% for more than one country.

SELECTION OF COUNTRIES TO INCLUDE IN THE
ANALYSIS:Countries included in the patent analysis were those with at least
1,400 inventors during the time periods of interest. Furthermore,countries were included only if at least 85% of inventors from thecountry had a gender inferred (according to the methods described in
the section “Author gender inference”).

INVENTOR GENDER INFERENCE:
As described in the section “Author gender inference,” a binary
gender was inferred for inventors using the NamSor API (January
2019 release). The API provides a Gender Probability Score and genderclassification based on three data points: country of origin, first nameand last name. To determine the gender of inventors, we relied on
first and last name only. First and last names were determined as
described in the next section. Once inventor names were parsed
into first and last name, these data were passed through NamSor
and gender was inferred based on the Gender Probability Score as
described in the section “Gender Probability Score.”

Methods and Experimental Approach PAGE 131

First and last name determination:

ACTIVE AUTHORS:

Names in PATSTAT are not consistently parsed into first names
and last names; in most cases, the format of names in PATSTAT is[lastName, firstName], but in other cases, the format is [firstName
lastName], without the comma. Because NamSor requires first andlast names to predict gender, we split names from PATSTAT into firstand last name components. We used the comma to delineate the firstsection of the string as the last name and the second part as the first
name. We used the absence of a comma as an indication that the firstsection of the string is the first name and the second section is thelast name.

Analyses of authors was limited to those authors who were active
during the period 2014–2018 (i.e., “active authors”). We defined“active authors” as those having published at least two publications(i.e., articles, reviews and/or conference papers) during the period ofinterest. To ensure inclusion of earliest career authors among thoseanalyzed, we also included authors in the period 2014–2018 if theirfirst Scopus-indexed publication occurred in that period. We applied a
two-publication minimum filter to ensure that we were analyzing theactive author population and not those who publish only occasionally.

Analysis of authors for case study on
China
We conducted tests to assess the accuracy of NamSor in predicting
the gender of Chinese names. Our initial assessment of NamSor
was done using a data set of 4,249 Olympic medalists that included
medalists’ first name, last name, country and gender. Because China
was under-represented among this data set (38 men and 64 women),
we assessed precision and recall for Chinese names using a set of
5,000 members of the Chinese Chemical Society, for whom first
name, last name and gender information was available. Names inthis data set were available in Mandarin only. Because the majorityof names in Scopus are captured using the Roman alphabet, theMandarin names were converted to Pinyin (the standard system ofapplying Romanized spelling to transliterate Chinese characters) using
the python Pinyin software package. These Pinyin names were tested
in NamSor for precision and recall using a threshold of 0.85, resulting
in a precision of 95% for men and 0.0% for women and a recall of
20.1% for men and 0.0% for women. However, when we ran the
Mandarin names through NamSor, the accuracy was much higher for
women without greatly impacting the accuracy for men (precision of
97.6% for men and 35.8% for women and recall of 21.9% for men and8.8% for women). We therefore decided to use Mandarin names as ameans of assessing the gender of researchers in China.

DATA SOURCE:
The data used for the analysis of Chinese authors were based on the
September 13, 2019 snapshot of the Scopus database.

PUBLICATIONS INCLUDED IN THE ANALYSIS:
Publications included in the analysis were selected as described in thesection Analysis of Bibliometric Data.

AUTHOR DEFINITION AND DISAMBIGUATION(SCOPUS AUTHOR PROFILES):
Authors were defined and disambiguated as described in the section
Analysis of Bibliometric Data.

AUTHORS INCLUDED IN THE ANALYSIS:This case study is based on authors who provided a Mandarin name as
an alternative author name in a Scopus-indexed publication publishedbetween 2014 and 2016.

PAGE 132 The Researcher Journey Through a Gender Lens

AUTHOR GENDER INFERENCE:
We determined the gender of authors included in this case study bypassing the Mandarin names of authors through the NamSor API(January 2019 release).

Name determination:
We retrieved Mandarin names from 1,795,177 publications publishedin 29,039 journals. Mandarin names were identified using a nicode
filter in python (called regex) that was used to test whether an“alternative name” was comprised of Mandarin characters.
Because Mandarin uses characters and not letters, the presence ofa character is sufficient for name identification. Therefore, there
was no need to exclude authors for whom only a single initial wasavailable as the author name, as described in the section “First name
determination” under Analysis of Bibliometric Data.

Gender Profitability Score:
We set a threshold for Prob(CLASSIFICATION) by testing against
a dataset of 5,000 members of the Chinese Chemical Society. The
dataset included each individual’s first and last name (in Mandarin
only) and self-identified gender. Based on NamSor precision andrecall with this dataset, we determined that the threshold for credibly
identifying the gender associated with a Mandarin name wasreached when the Calibrated Probability parameter returned by the
API was ≥70% (i.e., Prob(CLASSIFICATION) ≥0.70). This impacts theprecision and recall of author gender matching and corresponds to arecall of 42.0% for men and 41.7% women and a precision of 96.3%
for men and 93.0% for women, resulting in an F1 of 0.59 for men
and 0.58 for women. Authors meeting this threshold remained in
the analysis and authors not meeting this threshold were tagged as
gender “unknown.”

AUTHOR SUBJECT AREA ASSIGNATION:
Authors were assigned to a subject area as described in the section
Analysis of Bibliometric Data.

AUTHOR PUBLICATION HISTORY:
We assessed author publication history as described in the section
Analysis of Bibliometric Data.

Elsevier’s 2019 researcher survey
SURVEY TOOL:
A branded Elsevier online survey available in English only wasused to examine researchers’ experiences and opinions related tocareer progression and diversity, specifically gender balance, within
scholarly research. The survey questions were designed to provide
insight on gender differences in job satisfaction, perception of work
culture, perception of gender balance, researchers network size andcollaborative activities, barriers and reasons why individuals leave
careers in research, and gender diversity policy. The survey took 15
minutes to complete (median average). Fieldwork took place inAugust 2019.

SURVEYED POPULATION:
Of 40,130 individuals who were randomly selected from a database of
3.6 million researchers to participate in the survey, 1,213 researchers
responded (3% response rate).

ANALYSIS OF RESULTS:
Responses were weighted to be representative of the global researcher
population by country (UNESCO 2014 data). Base sizes shown were
unweighted unless otherwise stated.

STATISTICAL TESTING:
The maximum error margin for 1,213 responses was ± 2.4% at a 90%
confidence level. When comparing men and women, we used a Z-testof proportion to identify differences between two independent groups(90% confidence level). Statistically significant differences indicate that
we can be 90% confident the difference is explained by gender(p < 0.10).

Qualitative analyses
ONLINE SURVEY TO PREPARE FOR THE
QUALITATIVE RESEARCH:
An online survey was designed to gain initial insights into thedivergency in “perceptions of gender diversity and equity.” The survey
had 24 questions: 17 closed-ended questions about demographic
information, career progression, organizational and workplaceenvironment and personal experience; 6 open-ended questions about
the perceptions of the development of gender diversity and equity;and 1 question about the willingness to be contacted and contact
information for a follow-up interview. The survey was first sent to
850 researchers from 84 countries in the Elsevier Advisory Panel, andthen was forwarded to a broader group of potential respondents via
members of Elsevier’s Global Strategic Network team.

DEFINING RESPONDENT CLUSTERS:
We received 453 responses in total, of which 423 had complete
responses to closed-ended questions. Thus, there were 423 valid
responses to the closed-ended questions and 257 valid responses tothe open-ended questions. The 423 responses to the closed-ended
questions revealed substantial differences between women and men
respondents on their understanding of the impact of gender oncareer progression and the organizational environment. However,
the results from a portion of the online survey were not statisticallysignificant, and we therefore decided not to publish them. Upon
coding and grouping the 257 open-ended answers from the survey,
we distinguished eight clusters of responses representing distinct
perceptions of the development of gender diversity and equity
in academia: four clusters among men respondents and fourclusters among women respondents. For brevity and visualization
purposes, we used the term “cluster” in the report to refer to similar
opinions on gender-related issues in academia as expressed byrespondents in the open-ended survey questions. Hence, “clusters”
do not necessarily represent homogeneous groups of people, but
homogeneous opinions.
We point out that the open-ended questions likely overrepresent theopinions of respondents with strong views on gender-related issues.
As Ovseiko et al. have pointed out in their study on women’s andmen’s perceptions of the Athena SWAN Charter, “the voluntary openended nature of questions in the survey might represent those withstrong views. Those who provide anonymous survey responses might
have been more inclined to express negative attitudes.”62

INTERVIEW OUTLINE DESIGN:
Based on the survey results, we designed the interview outline toachieve two goals: (1) to confirm the interviewees’ perceptions ofgender-related issues in academia as they reported in the survey and(2) to identify the underlying reasons for the differences in perceptionsof gender-related issues.
The interview outline was composed of three parts: i) socioeconomic, cultural, organizational and family backgroundinformation; ii) attitudes to gender-related issues in academia
and their personal experience with these issues and iii) existing
intervention policies and suggestions of future interventions toachieve gender diversity and equity.

INTERVIEWEE SELECTION:
We followed this rule of criterion sampling to select interviewees:“Criterion sampling involves reviewing and studying ‘all casesthat meet some predetermined criterion of importance’.”63 We
contacted 2-4 researchers from each of the eight viewpoint clusters
who provided their contact information in the survey. A total of 30
women and 20 men survey respondents were invited to participate
in individual interviews, which were conducted remotely. Interviews
were conducted with 25 researchers total, 14 men and 11 women.
The interviewees were geographically diverse, with 6 from EU, 6 from
Asia, 1 from Russia, 3 from Australia, 2 from the USA and 3 from Latin
America. No survey respondents from Africa were interviewed.

ANALYSIS OF QUALITATIVE DATA:
Despite the use of an interview outline with a predetermined setof questions, the discussions with the interviewees covered many
subtopics within the topic of gender-related issues in academia. Thus,
the interview data was coded by the subtopics that emerged during
the interviews. The 25 interview recordings were transcribed andcoded using MaxQDA. Codes were grouped under each subtopic.

62 Ovseiko, P. V., Chapple, A., Edmunds, L. D., & Ziebland, S. (2017). Advancing gender equality through the Athena SWAN Charter for Women in Science: an exploratory study of women’s and men’s perceptions. Health Research Policy and
Systems, 15(1), 12. doi: 10.1186/s12961-017-0177-9
63 Suri, H. (2011). Purposeful sampling in qualitative research synthesis. Qualitative Research Journal, 11(2), 63-75. doi: 10.3316/QRJ1102063

Methods and Experimental Approach PAGE 133

Appendix B

Supplemental Data
FIGURE B.1

B.1

Percent of active authors
during the period 2014–2018 categorized basedon author publication
history.

KEY

GROUP

YEAR OF FIRSTPUBLICATION

A

2003 or priorB

2004–2008C

2009–2013D

2014–2018

Percent

0

10

20

30

40

50

60

70

80

90

100

Percent

0

10

20

30

40

50

60

70

80

90

100

Argentina

BrazilMexicoCanada

USA

EU28

UK

Portugal

Spain

France

Italy

Netherlands

Germany

Denmark

Australia

Japan

PAGE 134 The Researcher Journey Through a Gender Lens

FIGURE B.2

b2

Percent of active authors
Dentistryduring the period
2014–
Decision Sciences
Veterinary2018 categorized based
Economics
Healtharea.
Professions
on author subject

Percent

0

10

20

30

40

50

60

70

80

90

100

Percent

0

10

20

30

40

50

60

70

80

90

100

Argentina

BrazilBusiness
Nursing

Psychology

Dentistry

MexicoEnergyArts and Humanities

Decision Sciences Pharmacology

CanadaChemical Engineering

Veterinary

Neuroscience

Economics

Immunology and Microbiology

Earth and Planetary Sciences

USA

Mathematics

Health ProfessionsEnvironmental Science
Business

Chemistry

Nursing

Social Sciences

Psychology
EnergyMaterials Science
Physics and Astronomy
Agricultural Sciences

UK

Computer Science
Engineering

Arts & Humanities Biochemistry
Pharmacology

EU28

Medicine

Chemical Engineering

Portugal

Spain

Neuroscience
Earth & Planetary
Sciences
Immunology &Microbiology

FranceItaly

Mathematics
Environmental Science

Netherlands

Chemistry
Materials Science

Germany

Social Sciences
Physics & Astronomy

Denmark

Agricultural Sciences
Computer Science

Australia

Engineering
Biochemistry

Japan

Medicine

Supplemental Data PAGE 135

FIGURE B.3

More men

B.3

Argentina
Ratio of women to men
BrazilMexic0among active authors
CanadaUSA
during the period 1999–
EU28
2003 and 2014–2018,UK
Portugaldisaggregated according
Spain
Franceto author subject area.
Italy

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Computer
Science

Netherlands
Germany

Mathematics

Denmark
Australia

KEY
1999–2003Japan

2014–2018
Physics &Astronomy

Argentina
BrazilMexicoCanadaUSA

Chemistry

EU28
UK
Portugal

France
Italy
Netherlands
Germany
Denmark

Physical Sciences

Spain

Australia

ChemicalEngineering

Materials
ScienceJapan

Engineering

EnergyEnvironmental
Science

Earth &
Planetary
Sciences

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

PAGE 136 The Researcher Journey Through a Gender Lens

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenFIGURE B.3 (CON’T)

More men

B.3

Argentina
Ratio of women to men
BrazilMexic0among active authors
CanadaUSA
during the period 1999–
EU28
2003 and 2014–2018,
UK
Portugaldisaggregated according
Spain
Franceto author subject area.
Italy

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Agricultural
Sciences

Netherlands
Germany

Pharmacology

Denmark
Australia

1999–2003
2014–2018

Argentina
BrazilJapan

Life Sciences

KEY

Neuroscience

MexicoCanadaImmunology& Microbiology

USA
EU28
UK
Portugal
Spain

BiochemistryFrance
Italy
Netherlands
Germany
Denmark

Veterinary

Australia
Japan

Health Sciences

Dentistry

HealthProfessions

Medicine

Nursing

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More women

Supplemental Data PAGE 137

FIGURE B.3 (CON’T)

More men

B.3

Argentina
Ratio of women to men
Brazilamong active authorsMexic0
Canadaduring the period 1999–
USA
EU28
2003 and 2014–2018, UK
Portugaldisaggregated according
Spain
to author subject area.France
Italy

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Psychology

Netherlands
Germany

Business

Denmark

KEY

Australia

1999–2003Japan

2014–2018

BrazilMexicoCanadaUSA

Economics

Social Sciences

Argentina

Social Sciences

EU28
UK
Portugal
Spain
FranceDecision
Sciences

Italy
Netherlands
Germany
Denmark
Australia

Arts &
Humanities

Japan
Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

PAGE 138 The Researcher Journey Through a Gender Lens

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenFIGURE B.4

More menb.4

Ratio of women to men
among active authors
during the period
2014–2018 in eachcountry disaggregated byauthor subject area andpublication history.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

A

Computer
ScienceB
C
DA

Mathematics

B
C
D

A

GROUP

YEAR OF FIRSTPUBLICATION

A

2003 or priorB

2004–2008C

2009–2013A

D

2014–2018B

Physics &Astronomy

ChemistryA

UK
Portugal

Physical Sciences

MexicoEU28

C
D

BrazilUSA

C
D

Argentina

CanadaB

ChemicalEngineering

B
C
D

A

Materials
Science

C
D

Spain
France

A

Italy

B

Netherlands

EngineeringC
D

Germany
Denmark

A

Australia

B

Japan

fig B.6

B

EnergyC
D

A

Environmental
ScienceB
C
D

A

Earth &
Planetary
Sciences

B
C
D

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More women

Supplemental Data PAGE 139

FIGURE B.4 (CON’T)

More menb.4

Ratio of women to men
among active authors
during the period
2014–2018 in eachcountry disaggregated byauthor subject area andpublication history.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

A

Agricultural
Sciences

B
C
D

A

Pharmacology

BC
D

YEAR OF FIRSTPUBLICATION

A

2003 or priorB

2004–2008C

2009–2013D

2014–2018

A

Life Sciences

GROUP

Neuroscience

B
C
D

A

Immunology& Microbiology

B
C
D

Argentina
BrazilA

MexicoB

Biochemistry

Canada

C
D

USA
EU28
UK

Veterinary

Portugal

B
C
D

Spain
France

A

Italy

B

Dentistry

Netherlands

Japan

Health Sciences

Australia

C
D

Germany
Denmarkfig B.7

A

A

HealthProfessions

B
C
D

A

Medicine

B
C
DA

Nursing

B
C
D

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

PAGE 140 The Researcher Journey Through a Gender Lens

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenFIGURE B.4 (CON’T)

More menb.4

Ratio of women to men
among active authors
during the period
2014–2018 in eachcountry disaggregated byauthor subject area andpublication history.

10

Parity between men and women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

More women111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

A

Psychology

B
C
D

A

Business

B
C
D

YEAR OF FIRSTPUBLICATION

A

2003 or priorB

2004–2008C

2009–2013D

2014–2018

A

Economics

Social Sciences

GROUP

A

Social Sciences

Decision
Sciences

Spain
France
Italy
Netherlands

B
C
D

EU28

Portugal

C

A

USA

UK

B

D

BrazilCanadaC
D

Argentina

MexicoB

A

Arts &
Humanities

B

fig B.8

C
D

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More women

Germany
Denmark
Australia
Japan

Supplemental Data PAGE 141

ANY
Argentina

FIGURE B.5

All authors
Percent of active authors
during the period 2014–2018 in each publication
history category withineach country, subject
area and authorship
position.

Percent of authors

0

50 100 0

Brazil50 100 0

CanadaMexico50 100 0

50 100 0

USA

EU28

UK

50 100 0

50 100 0

50 100 0

Portugal

50 100Chemical Engineering
ChemistryComputer Science
Earth and Planetary Sciences
EnergyEngineering
Environmental Science
Materials Science
Mathematics
Physics and Astronomy
Agricultural Sciences
Biochemistry
Immunology and Microbiology

KEY

POSITION
2003 or prior
2004–2008

Neuroscience
Pharmacology
Dentistry
Health Professions

2009–2013

Medicine

2014–2018

Nursing
Veterinary
Arts and Humanities
Business
Decision Sciences
Economics
Psychology
Social Sciences
Spain

Percent of authors

Chemical Engineering
ChemistryComputer Science
Earth and Planetary Sciences
EnergyEngineering
Environmental Science
Materials Science
Mathematics
Physics and Astronomy
Agricultural Sciences
Biochemistry
Immunology and Microbiology
Neuroscience
Pharmacology
Dentistry
Health Professions
Medicine
Nursing
Veterinary
Arts and Humanities
Business
Decision Sciences
Economics
Psychology
Social Sciences

PAGE 142 The Researcher Journey Through a Gender Lens

0

50 100 0

France50 100 0

Italy

Netherlands

50 100 0

50 100 0

Germany

50 100 0

Denmark

50 100 0

Australia

50 100 0

Japan

50 100Corresponding
Argentina

FIGURE B.5 (CON'T)

Corresponding authors
Percent of active authors
during the period 2014–2018 in each publication
history category withineach country, subject
area and authorship
position.

Percent of authors

0

50 100 0

Brazil50 100 0

CanadaMexico50 100 0

50 100 0

USA

EU28

GBR

50 100 0

50 100 0

50 100 0

Portugal

50 100Chemical Engineering
ChemistryComputer Science
Earth and Planetary Sciences
EnergyEngineering
Environmental Science
Materials Science
Mathematics
Physics and Astronomy
Agricultural Sciences
Biochemistry
Immunology and Microbiology

KEY

POSITION
2003 or prior
2004–2008

Neuroscience
Pharmacology
Dentistry
Health Professions

2009–2013

Medicine

2014–2018

Nursing
Veterinary
Arts and Humanities
Business
Decision Sciences
Economics
Psychology
Social Sciences
Spain

Percent of authors

0

50 100 0

France50 100 0

Italy

Netherlands

50 100 0

50 100 0

Germany

50 100 0

Denmark

50 100 0

Australia

50 100 0

Japan

50 100Chemical Engineering
ChemistryComputer Science
Earth and Planetary Sciences
EnergyEngineering
Environmental Science
Materials Science
Mathematics
Physics and Astronomy
Agricultural Sciences
Biochemistry
Immunology and Microbiology
Neuroscience
Pharmacology
Dentistry
Health Professions
Medicine
Nursing
Veterinary
Arts and Humanities
Business
Decision Sciences
Economics
Psychology
Social Sciences

Supplemental Data PAGE 143

FirstArgentina

FIGURE B.5 (CON'T)

First authors
Percent of active authors
during the period 2014–2018 in each publication
history category withineach country, subject
area and authorship
position.

Percent of authors

0

50 100 0

Brazil50 100 0

CanadaMexico50 100 0

50 100 0

USA

EU28

UK

50 100 0

50 100 0

50 100 0

Portugal

50 100Chemical Engineering
ChemistryComputer Science
Earth and Planetary Sciences
EnergyEngineering
Environmental Science
Materials Science
Mathematics
Physics and Astronomy
Agricultural Sciences
Biochemistry
Immunology and Microbiology

KEY

POSITION

Neuroscience

2003 or prior

Pharmacology

2004–2008
2009–20132014–2018

Dentistry
Health Professions
Medicine
Nursing
Veterinary
Arts and Humanities
Business
Decision Sciences
Economics
Psychology
Social Sciences
Spain

Percent of authors

Chemical Engineering
ChemistryComputer Science
Earth and Planetary Sciences
EnergyEngineering
Environmental Science
Materials Science
Mathematics
Physics and Astronomy
Agricultural Sciences
Biochemistry
Immunology and Microbiology
Neuroscience
Pharmacology
Dentistry
Health Professions
Medicine
Nursing
Veterinary
Arts and Humanities
Business
Decision Sciences
Economics
Psychology
Social Sciences

PAGE 144 The Researcher Journey Through a Gender Lens

0

50 100 0

France50 100 0

Italy

Netherlands

50 100 0

50 100 0

Germany

50 100 0

Denmark

50 100 0

Australia

50 100 0

Japan

50 100Last
Argentina

FIGURE B.5 (CON'T)

Last authors
Percent of active authors
during the period 2014–2018 in each publication
history category withineach country, subject
area and authorship
position.

Percent of authors

0

50 100 0

Brazil50 100 0

CanadaMexico50 100 0

50 100 0

USA

EU28

GBR

50 100 0

50 100 0

50 100 0

Portugal

50 100Chemical Engineering
ChemistryComputer Science
Earth and Planetary Sciences
EnergyEngineering
Environmental Science
Materials Science
Mathematics
Physics and Astronomy
Agricultural Sciences
Biochemistry
Immunology and Microbiology

KEY

POSITION

Neuroscience

2003 or prior

Pharmacology

2004–2008
2009–20132014–2018

Dentistry
Health Professions
Medicine
Nursing
Veterinary
Arts and Humanities
Business
Decision Sciences
Economics
Psychology
Social Sciences
Spain

Percent of authors

0

50 100 0

France50 100 0

Italy

Netherlands

50 100 0

50 100 0

Germany

50 100 0

Denmark

50 100 0

Australia

50 100 0

Japan

50 100Chemical Engineering
ChemistryComputer Science
Earth and Planetary Sciences
EnergyEngineering
Environmental Science
Materials Science
Mathematics
Physics and Astronomy
Agricultural Sciences
Biochemistry
Immunology and Microbiology
Neuroscience
Pharmacology
Dentistry
Health Professions
Medicine
Nursing
Veterinary
Arts and Humanities
Business
Decision Sciences
Economics
Psychology
Social Sciences

Supplemental Data PAGE 145

b.6
More men

FIGURE B.6

Ratio of women to men
among active authors
during the period 1999–
2003 in each country
disaggregated based on
authorship position.

10

More women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Group A

Argentina

Group B
Group CGroup DA

BrazilB
CD
A

Mexico

B
C
D
A

KEY

GROUP

POSITIONAAll Authors

B

Corresponding
Authors

C

First Authors

D

Last Authors

Canada

B
C
D
A

USA

B
C
D
A

EU28

B
C
D
A
B

UK

C
D
A

Portugal

B
C
D
A

Spain

B
C
D
A

FranceBC

fig B.10

D
A

Italy

B
C
D
A

Netherlands

B
C
D
A

Germany

B
C
DA

Denmark

B
C
D
A

Australia

B
C
D
A

Japan

B
C
D

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

PAGE 146 The Researcher Journey Through a Gender Lens

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenb.7
FIGURE B.7

Ratio of women to men
among active authors
during the period 2014–2018 in each country
and authorship position
normalized to the ratio
among active authors
overall. Each circle
represents a different
country analyzed in thisreport.

Ratio of women to men normalized
to the ratio among all authors

0.0

0.1

0.2

0.3

0.4

0.5

Women are more represented in theauthor group than among all authors

Ratio is equivalent to ratio of
women to men among all authors

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

Computer
Science

Mathematics

Physics &Astronomy

POSITION
Corresponding
Authors

Chemistry

First Authors
Last Authors

Physical Sciences

KEY

Men are more represented in theauthor group than among all authors

ChemicalEngineering

fig B.11

Materials Science

Engineering

EnergyEnvironmental
Science

Earth &
Planetary Sciences

Ratio of women to men normalized
to the ratio among all authors

0.0

0.1

0.2

0.3

0.4

0.5

Men are more represented in theauthor group than among all authors

Women are more represented in theauthor group than among all authors

Supplemental Data PAGE 147

b.7
Ratio of women to men
among active authors
during the period 2014–2018 in each country
and authorship position
normalized to the ratio
among active authors
overall. Each circle
represents a different
country analyzed in thisreport.

KEY

Ratio of women to men normalized
to the ratio among all authors

Women are more represented in theauthor group than among all authors

Ratio is equivalent to ratio of
women to men among all authors

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

1.5

1.6

1.7

1.8

1.9

2.0

Agricultural
Sciences

Pharmacology

Life Sciences

FIGURE B.7 (CON’T)

Men are more represented in theauthor group than among all authors

Neuroscience

POSITION
Corresponding
Authors

Immunology& Microbiology

First Authors
Last Authors

Biochemistry

Veterinary

Health Sciences

Dentistry

HealthProfessions

Medicine

Nursing

Ratio of women to men normalized
to the ratio among all authors

Men are more represented in theauthor group than among all authors

PAGE 148 The Researcher Journey Through a Gender Lens

Women are more represented in theauthor group than among all authorsb.7
Ratio of women to men
among active authors
during the period 2014–2018 in each country
and authorship position
normalized to the ratio
among active authors
overall. Each circle
represents a different
country analyzed in thisreport.
KEY

POSITION
Corresponding
Authors
First Authors

Ratio of women to men normalized
to the ratio among all authors

Women are more represented in theauthor group than among all authors

Ratio is equivalent to ratio of
women to men among all authors

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

1.5

1.6

1.7

1.8

1.9

2.0

Psychology

Business

Economics

Social Sciences

FIGURE B.7 (CON’T)

Men are more represented in theauthor group than among all authors

Social Sciences

Last Authors

Decision
Sciences

Arts &
Humanities

Ratio of women to men normalized
to the ratio among all authors

Men are more represented in theauthor group than among all authors

Women are more represented in theauthor group than among all authors

Supplemental Data PAGE 149

b.8
FIGURE B.8

Ratio of women to men
among active authors
during the period 2014–2018 in medicine andsubfields of medicine.

More men

10

More women

Women per 100 men

0

20

30

40

50

60

Men per 100 women∞ 1000 500 333 250 200 167

70

80

90

143 125

111

100

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

111

125 143

167 200 250 333 500 1000 ∞

90

80

60

70

50

40

30

20

10

0

Pharmacology

Neurosciences
Imunology &Microbiology

Argentina
BrazilMexicoCanadaUSA
EU28
UK
Portugal
Spain
FranceBiochemistry

Medicine
General Clinical
Medicine
Pediatrics
Emergency
Medicine

Italy
Netherlands
Germany
Denmark
Australia
Japan

Surgery
Radiology &Imaging
Diabetes &Endocrinology
Cardiology &Pulmonology
CancerFertility & Birth
Infectious
Diseases & Allergy
Public Health

Women per 100 men

0Men per 100 women∞ 1000 500 333 250 200 167

10More men

PAGE 150 The Researcher Journey Through a Gender Lens

20

30

40

50

60

80

90

143 125

70

111

100

70

50

40

30

20

10

0

More womenFIGURE B.9

b.9

Ratio of women to men
authors versus ratio of
the average number ofpublications by women
to men in each country(among authors active inthe period 2014–2018).
Data analyzed for authors
in each authorship
position as shown.

Ratio of women to men

0.0

0.2

0.4

0.6

0.8

1.0

1.2
1.0
0.9
0.8

All Authors
0.7
0.6
0.5
1.0

Argentina
Brazil0.8

Corresponding
Authors

0.7

Mexico0.6

Canada
USA

0.5

EU28

1.0

UK

0.9

Portugal
Spain
France0.8

First Authors
0.7

Italy
Netherlands

0.6

Germany
Denmark

0.5

Australia

1.0

Japan

Ratio of average number of publications by women to those by men

0.9

0.9
0.8

Last Authors
0.7
0.6
0.5
0.0

0.2

0.4

0.6

0.8

1.0

1.2

Supplemental Data PAGE 151

FIGURE B.10

b.10

Ratio of average
publication count of
men to women in eachcountry, disaggregated byauthor position and yearof first publication.

GROUP

YEAR OF FIRSTPUBLICATION

A

2003 or priorB

2004–2008C

2009–2013D

2014–2018

Argentina
BrazilMexicoCanadaUSA
EU28
UK
Portugal
Spain
France
Italy
Netherlands
Germany
Denmark
Australia
Japan

PAGE 152 The Researcher Journey Through a Gender Lens

Men are cited more

Parity between men and women

Women to men 0.50 0.53 0.56 0.59 0.63
Men to women

2.0

1.9

1.8

1.7

1.6

0.67 0.71 0.77 0.83 0.91
1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

Women are cited more

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50

A

All Authors

B
C
D

A

Corresponding
Authors

B
C
D

A

First Authors

B
C
D

A

Last Authors

B
C
D

Women per 100 men 0.50 0.53 0.56 0.59 0.63
Men per 100 women

2.0

1.9

1.8

1.7

Men are cited more

1.6

0.67 0.71 0.77 0.83 0.91
1.5

1.4

1.3

1.2

1.1

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.91 0.83 0.77 0.71 0.67 0.63 0.59 0.56 0.53 0.50
Women are cited more

B.11

Percent of women andArgentina
Brazilmen in each country
Mexic0
Canadarelative to the numberofUSA
authors in the cohort
in
EU28
UK
2000. Cohort isPortugal
definedSpainas those whoseFrance
first
Italy
publication wasNetherlands
in 1999
Germany atand who published
Denmark
Australia
least two publications.

2000

2001

2002

2003

2004

2005

2006

2007

2008

2010

2011

2012

2013

2014

2015

2016

2017

2018

2009

100
90
80
70
60
Women

FIGURE B.11

50
40
30
20
10

Japan

0
100
90

Brazil80

Mexico70

Canada

60

USA

50

EU28

Men

Argentina

40

UK

30

Portugal

20

Spain

10

France0Percent

Italy
Netherlands

100

Germany90

Denmark

80

Australia

70

Japan
Women

60
50
40
30
20
10
0
100
90
80
70

Men

60
50
40
30
20
10
0

Supplemental Data PAGE 153

b.12

FIGURE B.12

Percentage of all authors
who first published ineach country or the
EU28 in 2009–2013 who
published again during
the period 2014–2018,disaggregated according
to whether they have everpublished outside theircountry of origin.

Percent

60

70

80

90

100

60

70

80

90

100

All publications
within countryof orgin

At least one
international
publication

Percent

Argentina
BrazilMexicoCanadaUSA
EU28
UK
Portugal

-40%

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

-40%

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

Spain
FranceItaly

2009–2013

Netherlands
Germany
Denmark
Australia

2014–2018Japan

2009–20132014–2018

PAGE 154 The Researcher Journey Through a Gender Lens

b.13 -- 1999
1999 pubs
pubs
b.13
FIGURE B.13

Argentina

Spain

BrazilFranceMexicoItaly

CanadaNetherlands

USA

Germany

EU28

Denmark

UK

Australia

Portugal

Japan

All
Allpublications
publicationswithin
withincountry
countryofoforigin
originAtAtleast
leastone
oneinternational
internationalpublication
publication

Average number ofpublications during
the period 2014–2018
among women and men
who first published in
2009–2013 and publishedagain in 2014–2018,disaggregated based onwhether they have everpublished internationally.

Average
AveragePublication Count
Publication Count

00

55

10
10

15
15

20
20

25
25

30
30

00

55

10
10

15
15

20
20

25
25

30
30

00

55

10
10

15
15

20
20

25
25

30
30

00

55

10
10

15
15

20
20

25
25

30
30

Women
Women

Men
Men

Women
Women

Men
Men

b.13
b.13 -- 20092009 pubs
pubs
FIGURE B.13 (CON'T)

Argentina

Spain

BrazilFranceMexicoItaly

CanadaNetherlands

USA

Germany

EU28

Denmark

UK

Australia

Portugal

Japan

All
Allpublications
publicationswithin
withincountry
countryofoforigin
originAtAtleast
leastone
oneinternational
internationalpublication
publication

Average number ofpublications during
the period 2014–2018
among women and men
who first published in
1999–2003 and publishedagain in 2014–2018,disaggregated based onwhether they have everpublished internationally.

Average
AveragePublication Count
Publication Count

Women
Women

Men
Men

Women
Women

Men
Men

Supplemental Data PAGE 155

b.13 - 1999 FWCIFIGURE B.13 (CON'T)

Average
Average
FWCI
FWCI

Argentina

Spain

BrazilFranceMexicoItaly

CanadaNetherlands

USA

Germany

EU28

Denmark

UK

Australia

PortugalJapanAt
At least
least one
one international
international publication
publicationAll
All publications
publications within
within country
country ofof originoriginAverage FWCI basedon publications during
the period 2014–2018
among women and men
who first published in
2009–2013 and publishedagain in 2014–2018,disaggregated based onwhether they have everpublished internationally.

0.0
0.0

0.2
0.2

0.4
0.4

0.6
0.6

0.8
0.8

1.0
1.0

1.2
1.2

1.4
1.4

1.6
1.6

1.8
1.8

2.0
2.0

0.0
0.0

0.2
0.2

0.4
0.4

0.6
0.6

0.8
0.8

1.0
1.0

1.2
1.2

1.4
1.4

1.6
1.6

1.8
1.8

2.0
2.0

0.0
0.0

0.2
0.2

0.4
0.4

0.6
0.6

0.8
0.8

1.0
1.0

1.2
1.2

1.4
1.4

1.6
1.6

1.8
1.8

2.0
2.0

0.0
0.0

0.2
0.2

0.4
0.4

0.6
0.6

0.8
0.8

1.0
1.0

1.2
1.2

1.4
1.4

1.6
1.6

1.8
1.8

2.0
2.0

Women

Men

Women

Men

b.13 - 2009 FWCIFIGURE B.13 (CON'T)

Argentina

Spain

BrazilFranceMexicoItaly

CanadaNetherlands

USA

Germany

EU28

Denmark

UK

Australia

Portugal

Japan

All
All publications
publications within
within country
country ofof originoriginAt
At least
least one
one international
international publication
publication

Average FWCI basedon publications during
the period 2014–2018
among women and men
who first published in
1999–2003 and publishedagain in 2014–2018,disaggregated based onwhether they have everpublished internationally.

Average
Average
FWCI
FWCI

PAGE 156 The Researcher Journey Through a Gender Lens

Women

Men

Women

Men

FIGURE B.14

B.14

Average share of men
collaborators (y-axis) offocal authors groupedbased on year of theirfirst publication (x-axis),
by region and subject
area.
The share of men collaborators is
computed as the ratio between
the count of direct collaborators
inferred to be men to the overall
count of direct collaborators ofa focal author. Average values
corresponding to less than 10
observations were excluded fromthe analysis.

BrazilAverage share ofmen collaborators

GROUP
A

1989–1993B

1994–1998

C

1999–2003D

2004–2008E

2009–2013

0.2

0.0

0.2

Japan

0.4

0.6

0.8 0.0

0.2

0.4

0.6

0.8 0.0

0.2

USA

0.4

0.6

0.8 0.0

0.2

0.4

0.6

0.8 0.0

0.2

EU28

0.4

0.6

0.8 0.0

0.2

0.4

0.6

0.8 0.0

0.2

0.4

0.6

0.8

0.4

0.6

0.8

Group B

Medicine

Group CGroup DGroup EA
B

Biochemistry

C
D
E
A
B

Engineering

C
D
E
A
B

Business &Economics

YEAR OF FIRSTPUBLICATION

0.0

C
D
E

Brazil

Japan

USA

EU28

Women
Men

Supplemental Data PAGE 157

TABLE B.1

Country

Active authors during the periods 2014–2018

GenderNumber and percent of men and women among authors ineach country and the EU28 overall and in each subject area.
Argentina

All
Agricultural Sciences
Arts and Humanities
BiochemistryBusiness
ChemicalEngineering
ChemistryComputer Science
Decision Sciences
Dentistry
Earth and Planetary
Sciences
Economics
EnergyEngineering
Environmental
Science
Health Professions
Immunology andMicrobiology
Materials Science
Mathematics
Medicine
Neuroscience
NursingPharmacology
Physics andAstronomy
Psychology
Social Sciences
Veterinary

BrazilMexico% of authors

Subject Area

CanadaUSA

Number of authors

EU28

UK

Portugal

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

48.98%

51.02%

55.75%

44.25%

61.89%

38.11%

62.40%

37.60%

66.38%

33.62%

61.49%

38.51%

62.53%

37.47%

51.68%

48.32%

23,21424,180195,430

155,132

57,14035,183

134,339

80,944

1,095,391

554,9111,430,141

895,802

232,464

139,31230,18928,22742.21%

57.79%

54.91%

45.09%

60.20%

39.80%

61.01%

38.99%

64.01%

35.99%

54.49%

45.51%

58.72%

41.28%

43.25%

56.75%

4,955

6,785

44,641

36,65812,046

7,965

14,971

9,566

96,64654,349136,607

114,084

18,774

13,199

3,260

4,278

48.21%

51.79%

54.75%

45.25%

56.23%

43.77%

52.57%

47.43%

57.26%

42.74%

56.90%

43.10%

55.96%

44.04%

48.14%

51.86%

1,282

1,377

3,606

2,980

1,507

1,173

5,088

4,591

37,92428,31164,05248,514

13,95010,980

1,089

1,173

39.05%

60.95%

47.25%

52.75%

53.92%

46.08%

60.22%

39.78%

64.95%

35.05%

51.49%

48.51%

58.19%

41.81%

38.82%

61.18%

3,760

5,869

25,59828,577

9,228

7,886

27,044

17,863242,074

130,656

246,533

232,274

43,26831,085

3,735

5,887

58.67%

41.33%

64.26%

35.74%

64.44%

35.56%

66.29%

33.71%

70.49%

29.51%

63.20%

36.80%

66.48%

33.52%

55.20%

44.80%

264

186

6,699

3,726

964

532

3,512

1,786

28,53011,94544,87826,136

8,794

4,434

1,443

1,171

46.75%

53.25%

55.48%

44.52%

63.00%

37.00%

76.33%

23.67%

77.54%

22.46%

64.91%

35.09%

74.18%

25.82%

46.01%

53.99%

1,100

1,253

7,866

6,312

3,297

1,936

6,996

2,170

51,196

14,831

72,361

39,11910,573

3,680

1,379

1,618

48.86%

51.14%

54.99%

45.01%

61.67%

38.33%

74.05%

25.95%

76.05%

23.95%

62.52%

37.48%

70.80%

29.20%

45.29%

54.71%

2,124

2,223

16,004

13,100

5,236

3,254

11,512

4,035

93,01929,293

138,618

83,087

19,861

8,190

2,322

2,805

74.24%

25.76%

79.61%

20.39%

77.09%

22.91%

82.35%

17.65%

82.67%

17.33%

79.67%

20.33%

81.07%

18.93%

73.74%

26.26%

2,297

797

24,909

6,380

7,784

2,313

18,457

3,957

137,841

28,902

225,873

57,621

28,226

6,590

7,295

2,598

62.69%

37.31%

67.63%

32.37%

64.96%

35.04%

78.26%

21.74%

80.85%

19.15%

73.52%

26.48%

77.26%

22.74%

65.56%

34.44%

205

122

5,529

2,646

482

260

1,998

555

14,017

3,321

23,420

8,436

3,350

986

813

427

48.10%

51.90%

47.54%

52.46%

55.58%

44.42%

64.45%

35.55%

67.58%

32.42%

59.94%

40.06%

62.31%

37.69%

51.20%

48.80%

76

82

5,654

6,238

259

207

631

348

6,207

2,977

10,426

6,967

1,754

1,061

278

265

54.71%

45.29%

68.65%

31.35%

69.41%

30.59%

76.42%

23.58%

79.18%

20.82%

71.05%

28.95%

74.41%

25.59%

59.56%

40.44%

1,895

1,569

9,384

4,286

3,499

1,542

9,506

2,933

65,06017,10889,97936,654

13,759

4,732

1,810

1,229

65.55%

34.45%

71.25%

28.75%

68.84%

31.16%

74.25%

25.75%

75.76%

24.24%

66.54%

33.46%

71.31%

28.69%

57.72%

42.28%

314

165

2,312

933

727

329

2,561

888

20,764

6,644

33,27816,737

6,628

2,667

658

482

68.60%

31.40%

76.66%

23.34%

76.03%

23.97%

84.99%

15.01%

85.80%

14.20%

77.92%

22.08%

82.69%

17.31%

69.71%

30.29%

664

304

9,266

2,821

2,816

888

6,946

1,227

53,908

8,924

72,141

20,447

10,172

2,129

1,728

751

67.25%

32.75%

75.49%

24.51%

76.37%

23.63%

84.06%

15.94%

84.38%

15.62%

79.26%

20.74%

83.04%

16.96%

69.83%

30.17%

2,826

1,376

32,764

10,64011,4493,542

28,381

5,381

226,061

41,838334,40987,492

42,745

8,728

8,147

3,520

43.05%

56.95%

59.19%

40.81%

61.59%

38.41%

66.15%

33.85%

68.75%

31.25%

62.08%

37.92%

66.94%

33.06%

48.49%

51.51%

1,895

2,507

17,936

12,367

6,195

3,864

12,0106,146

72,487

32,953

107,483

65,66015,884

7,844

2,895

3,075

50.38%

49.62%

53.18%

46.82%

55.98%

44.02%

44.57%

55.43%

53.08%

46.92%

56.63%

43.37%

55.07%

44.93%

58.69%

41.31%

199

196

5,364

4,723

323

254

2,946

3,664

21,75819,23624,14018,490

4,795

3,912

780

549

34.94%

65.06%

42.30%

57.70%

51.97%

48.03%

56.00%

44.00%

59.95%

40.05%

46.99%

53.01%

53.70%

46.30%

34.93%

65.07%

1,554

2,894

9,225

12,585

3,338

3,085

5,631

4,424

51,79434,60357,36164,703

10,118

8,724

1,055

1,965

58.50%

41.50%

66.58%

33.42%

71.06%

28.94%

82.57%

17.43%

83.47%

16.53%

74.51%

25.49%

80.58%

19.42%

59.77%

40.23%

1,662

1,179

14,892

7,474

6,157

2,508

12,861

2,714

113,115

22,398

169,532

58,002

20,906

5,037

2,881

1,939

72.62%

27.38%

79.72%

20.28%

80.13%

19.87%

83.98%

16.02%

84.04%

15.96%

80.54%

19.46%

83.20%

16.80%

73.08%

26.92%

1,541

581

11,365

2,891

4,513

1,119

8,926

1,703

66,194

12,569123,527

29,84915,437

3,116

2,926

1,078

45.13%

54.87%

47.26%

52.74%

54.66%

45.34%

52.19%

47.81%

58.70%

41.30%

52.07%

47.93%

54.36%

45.64%

42.49%

57.51%

8,173

9,938

56,15062,666

16,594

13,76447,176

43,210407,756

286,876

457,409421,024

83,58270,162

8,528

11,54145.31%

54.69%

45.67%

54.33%

54.77%

45.23%

53.88%

46.12%

60.28%

39.72%

49.31%

50.69%

53.81%

46.19%

40.55%

59.45%

898

1,084

4,990

5,937

1,677

1,385

7,465

6,389

56,98337,55352,58454,051

10,345

8,881

888

1,302

30.47%

69.53%

26.97%

73.03%

38.65%

61.35%

31.61%

68.39%

34.23%

65.77%

37.43%

62.57%

36.64%

63.36%

33.76%

66.24%

181

413

3,464

9,380

841

1,335

2,402

5,197

19,63037,71920,804

34,770

5,187

8,968

371

728

37.46%

62.54%

42.34%

57.66%

50.95%

49.05%

58.91%

41.09%

63.53%

36.47%

49.37%

50.63%

59.15%

40.85%

33.04%

66.96%

777

1,297

7,867

10,715

2,248

2,164

4,059

2,831

50,84429,193

46,82048,011

8,510

5,878

814

1,650

67.01%

32.99%

71.10%

28.90%

75.07%

24.93%

83.43%

16.57%

84.44%

15.56%

78.65%

21.35%

81.35%

18.65%

67.96%

32.04%

2,539

1,250

16,621

6,755

7,066

2,347

14,377

2,856

127,437

23,475

209,691

56,92927,904

6,396

2,931

1,382

39.85%

60.15%

37.69%

62.31%

46.68%

53.32%

39.11%

60.89%

44.26%

55.74%

41.67%

58.33%

39.98%

60.02%

33.62%

66.38%

428

646

2,734

4,519

1,021

1,166

4,456

6,937

35,81945,10733,93247,4897,474

11,221810

1,599

43.59%

56.41%

54.80%

45.20%

55.51%

44.49%

48.63%

51.37%

52.62%

47.38%

56.00%

44.00%

54.06%

45.94%

48.08%

51.92%

1,965

2,543

15,344

12,654

4,461

3,575

12,725

13,440103,123

92,839134,890

105,979

28,57024,274

3,412

3,685

44.04%

55.96%

51.21%

48.79%

66.64%

33.36%

47.71%

52.29%

51.23%

48.77%

47.39%

52.61%

48.87%

51.13%

40.42%

59.58%

617

784

9,172

8,740

1,598

800

1,145

1,255

7,346

6,992

13,23014,685

1,950

2,040

249

367

PAGE 158 The Researcher Journey Through a Gender Lens

TABLE B.1 (CON’T)

Country

Active authors during the periods 2014–2018

GenderNumber and percent of men and women among authors ineach country and the EU28 overall and in each subject area.
Spain

All
Agricultural Sciences
Arts and Humanities
BiochemistryBusiness
ChemicalEngineering
ChemistryComputer Science
Decision Sciences
Dentistry
Earth and Planetary
Sciences
Economics
EnergyEngineering
Environmental
Science
Health Professions
Immunology andMicrobiology
Materials Science
Mathematics
Medicine
Neuroscience
NursingPharmacology
Physics andAstronomy
Psychology
Social Sciences
Veterinary

FranceItaly% of authors

Subject Area

Netherlands

Germany

Denmark

Number of authors

Australia

Japan

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

56.19%

43.81%

61.09%

38.91%

56.24%

43.76%

67.10%

32.90%

67.98%

32.02%

64.76%

35.24%

60.54%

39.46%

84.78%

15.22%

141,085

110,017

169,294

107,837

145,603113,292

71,25534,940278,272

131,043

30,78916,75699,35564,763363,941

65,32352.07%

47.93%

53.33%

46.67%

51.02%

48.98%

65.58%

34.42%

55.80%

44.20%

61.61%

38.39%

62.59%

37.41%

78.96%

21.04%

15,885

14,621

16,83814,736

13,571

13,026

6,846

3,593

22,142

17,538

3,443

2,145

13,673

8,173

29,658

7,901

58.16%

41.84%

56.10%

43.90%

56.23%

43.77%

61.36%

38.64%

61.31%

38.69%

63.06%

36.94%

49.41%

50.59%

79.28%

20.72%

9,384

6,752

7,131

5,581

5,920

4,608

2,996

1,887

8,023

5,064

1,135

665

4,148

4,247

2,253

589

47.15%

52.85%

48.98%

51.02%

41.70%

58.30%

62.09%

37.91%

55.67%

44.33%

59.28%

40.72%

58.78%

41.22%

79.18%

20.82%

21,91024,55630,60431,87324,33834,033

14,466

8,834

50,65240,337

6,900

4,739

17,068

11,96880,443

21,15459.43%

40.57%

62.88%

37.12%

59.16%

40.84%

71.63%

28.37%

71.90%

28.10%

67.96%

32.04%

63.77%

36.23%

83.84%

16.16%

3,717

2,537

3,588

2,118

3,506

2,420

2,730

1,081

9,311

3,639

1,084

511

4,280

2,432

2,486

479

55.83%

44.17%

63.70%

36.30%

55.96%

44.04%

77.74%

22.26%

71.44%

28.56%

74.96%

25.04%

77.35%

22.65%

86.27%

13.73%

6,024

4,766

9,316

5,309

5,288

4,162

3,420

979

18,239

7,292

1,566

523

4,155

1,217

20,8643,321

55.01%

44.99%

61.79%

38.21%

52.22%

47.78%

76.90%

23.10%

70.93%

29.07%

73.34%

26.66%

74.07%

25.93%

85.07%

14.93%

11,812

9,661

18,32011,33010,190

9,325

5,723

1,719

34,915

14,307

2,768

1,006

7,460

2,611

45,556

7,994

75.54%

24.46%

79.70%

20.30%

74.29%

25.71%

83.24%

16.76%

84.20%

15.80%

82.76%

17.24%

81.92%

18.08%

92.44%

7.56%

19,882

6,437

28,835

7,344

20,437

7,072

9,846

1,982

50,012

9,386

3,952

823

11,0532,440

47,106

3,854

67.96%

32.04%

75.20%

24.80%

66.50%

33.50%

79.99%

20.01%

79.73%

20.27%

79.58%

20.42%

77.85%

22.15%

91.16%

8.84%

1,754

827

2,796

922

2,009

1,012

1,191

298

5,402

1,373

456

117

1,385

394

2,320

225

57.46%

42.54%

60.12%

39.88%

67.69%

32.31%

65.46%

34.54%

62.58%

37.42%

60.79%

39.21%

65.34%

34.66%

77.96%

22.04%

1,205

892

677

449

1,833

875

472

249

1,960

1,172

138

89

509

270

4,209

1,190

68.24%

31.76%

70.51%

29.49%

68.26%

31.74%

80.63%

19.37%

75.31%

24.69%

78.42%

21.58%

76.43%

23.57%

89.61%

10.39%

7,878

3,666

13,196

5,519

10,327

4,802

4,362

1,048

16,504

5,410

1,472

405

8,138

2,509

13,5591,572

62.85%

37.15%

66.42%

33.58%

63.18%

36.82%

76.82%

23.18%

72.32%

27.68%

72.11%

27.89%

72.42%

27.58%

88.86%

11.14%

2,982

1,763

3,753

1,897

3,121

1,819

1,939

585

5,990

2,293

706

273

3,059

1,165

1,810

227

71.20%

28.80%

76.83%

23.17%

73.84%

26.16%

82.76%

17.24%

83.06%

16.94%

84.56%

15.44%

85.29%

14.71%

93.87%

6.13%

5,973

2,416

8,189

2,470

7,327

2,596

3,268

681

15,670

3,197

2,185

399

4,261

735

17,321

1,132

74.14%

25.86%

79.17%

20.83%

74.53%

25.47%

84.70%

15.30%

84.30%

15.70%

83.18%

16.82%

83.15%

16.85%

93.40%

6.60%

26,206

9,142

40,991

10,786

31,215

10,666

13,4492,430

76,206

14,196

5,622

1,137

17,2693,499

97,021

6,857

59.16%

40.84%

61.09%

38.91%

59.07%

40.93%

72.45%

27.55%

66.66%

33.34%

69.39%

30.61%

67.09%

32.91%

86.00%

14.00%

10,7807,442

12,215

7,780

10,639

7,373

5,674

2,158

17,878

8,941

2,680

1,182

10,354

5,080

16,3242,658

61.65%

38.35%

59.83%

40.17%

49.56%

50.44%

59.01%

40.99%

61.53%

38.47%

57.21%

42.79%

47.19%

52.81%

81.51%

18.49%

3,424

2,130

2,267

1,522

1,991

2,026

1,388

964

3,404

2,128

603

451

2,998

3,355

5,078

1,152

42.69%

57.31%

45.01%

54.99%

39.75%

60.25%

57.38%

42.62%

49.42%

50.58%

56.12%

43.88%

55.07%

44.93%

76.38%

23.62%

5,189

6,965

7,879

9,626

5,442

8,250

3,607

2,679

11,573

11,843

1,678

1,312

4,125

3,366

13,3884,14065.98%

34.02%

74.43%

25.57%

67.88%

32.12%

84.18%

15.82%

80.39%

19.61%

82.22%

17.78%

83.07%

16.93%

91.90%

8.10%

11,143

5,745

24,4968,414

12,472

5,902

6,753

1,269

44,753

10,915

2,484

537

8,228

1,677

57,072

5,032

76.97%

23.03%

80.26%

19.74%

73.70%

26.30%

85.19%

14.81%

84.64%

15.36%

87.54%

12.46%

84.56%

15.44%

92.87%

7.13%

10,132

3,031

18,374

4,520

11,461

4,089

5,441

946

27,695

5,025

2,058

293

5,077

927

19,6591,510

48.36%

51.64%

49.81%

50.19%

48.06%

51.94%

58.35%

41.65%

56.80%

43.20%

55.07%

44.93%

51.71%

48.29%

80.66%

19.34%

52,22655,777

48,384

48,74457,42562,05428,39020,26473,54755,934

11,6089,470

36,72634,293134,044

32,13344.73%

55.27%

47.21%

52.79%

41.15%

58.85%

55.90%

44.10%

51.70%

48.30%

54.86%

45.14%

52.37%

47.63%

78.21%

21.79%

4,075

5,035

5,921

6,620

5,939

8,495

3,419

2,697

12,213

11,412

1,258

1,035

4,248

3,863

12,361

3,443

37.69%

62.31%

35.23%

64.77%

38.56%

61.44%

43.47%

56.53%

46.08%

53.92%

35.47%

64.53%

28.94%

71.06%

63.78%

36.22%

3,995

6,606

2,641

4,855

1,694

2,699

1,152

1,498

2,081

2,435

476

866

2,348

5,765

3,627

2,060

43.10%

56.90%

47.34%

52.66%

39.67%

60.33%

60.90%

39.10%

55.03%

44.97%

55.39%

44.61%

58.36%

41.64%

76.90%

23.10%

4,280

5,650

5,314

5,911

4,794

7,290

2,544

1,633

7,952

6,497

1,212

976

2,820

2,012

18,8295,655

74.15%

25.85%

77.80%

22.20%

74.10%

25.90%

84.71%

15.29%

82.93%

17.07%

85.55%

14.45%

82.53%

17.47%

92.66%

7.34%

14,844

5,176

32,7599,349

20,126

7,035

8,695

1,569

54,622

11,244

3,577

604

8,349

1,767

64,5345,114

44.84%

55.16%

41.39%

58.61%

35.36%

64.64%

47.54%

52.46%

43.37%

56.63%

48.17%

51.83%

35.93%

64.07%

72.32%

27.68%

4,310

5,303

3,218

4,557

2,786

5,093

2,776

3,063

5,908

7,713

567

610

3,217

5,737

2,814

1,077

56.74%

43.26%

56.41%

43.59%

55.20%

44.80%

61.44%

38.56%

60.93%

39.07%

60.99%

39.01%

48.00%

52.00%

81.59%

18.41%

19,26014,684

11,5198,900

11,048

8,968

7,938

4,982

18,315

11,744

2,758

1,764

12,134

13,144

8,560

1,932

49.70%

50.30%

49.77%

50.23%

45.34%

54.66%

59.23%

40.77%

41.97%

58.03%

46.75%

53.25%

52.62%

47.38%

77.16%

22.84%

1,402

1,419

1,311

1,323

1,655

1,995

462

318

1,648

2,279

302

344

1,106

996

2,558

757

Supplemental Data PAGE 159

TABLE B.1 (CON’T)

Country

Active authors during the periods 1999–2003

GenderNumber and percent of men and women among authors ineach country and the EU28 overall and in each subject area.
Argentina

All
Agricultural Sciences
Arts and Humanities
BiochemistryBusiness
ChemicalEngineering
ChemistryComputer Science
Decision Sciences
Dentistry
Earth and Planetary
Sciences
Economics
EnergyEngineering
Environmental
Science
Health Professions
Immunology andMicrobiology
Materials Science
Mathematics
Medicine
Neuroscience
NursingPharmacology
Physics andAstronomy
Psychology
Social Sciences
Veterinary

BrazilMexico% of authors

Subject Area

CanadaUSA

Number of authors

EU28

UK

Portugal

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

53.49%

46.51%

64.70%

35.30%

69.19%

30.81%

72.48%

27.52%

75.50%

24.50%

70.73%

29.27%

72.20%

27.80%

61.44%

38.56%

8,224

7,152

30,073

16,407

12,077

5,377

57,263

21,741

519,241

168,538

632,082

261,533

114,706

44,168

6,682

4,193

46.84%

53.16%

63.90%

36.10%

67.18%

32.82%

73.85%

26.15%

75.14%

24.86%

65.69%

34.31%

71.24%

28.76%

49.67%

50.33%

1,631

1,851

5,476

3,093

2,299

1,123

7,348

2,602

46,12815,262

57,86230,228

10,596

4,277

824

835

50.31%

49.69%

60.47%

39.53%

58.99%

41.01%

61.81%

38.19%

65.33%

34.67%

67.96%

32.04%

66.37%

33.63%

53.29%

46.71%

82

81

153

100

82

57

1,685

1,041

14,1397,503

14,367

6,773

5,046

2,557

89

78

42.40%

57.60%

51.43%

48.57%

57.50%

42.50%

66.56%

33.44%

70.54%

29.46%

59.95%

40.05%

65.96%

34.04%

45.10%

54.90%

1,951

2,650

4,956

4,680

2,029

1,500

13,5686,818

125,888

52,582

135,314

90,39425,38013,097

1,118

1,361

59.52%

40.48%

80.67%

19.33%

74.62%

25.38%

75.17%

24.83%

77.39%

22.61%

76.56%

23.44%

74.67%

25.33%

74.27%

25.73%

50

34

242

58

97

33

1,202

397

14,006

4,091

10,849

3,322

4,069

1,380

127

44

56.28%

43.72%

64.32%

35.68%

72.60%

27.40%

83.00%

17.00%

84.85%

15.15%

73.88%

26.12%

80.38%

19.62%

56.75%

43.25%

551

428

1,372

761

710

268

3,437

704

23,226

4,146

32,068

11,337

5,179

1,264

429

327

50.12%

49.88%

62.12%

37.88%

68.40%

31.60%

79.06%

20.94%

81.95%

18.05%

70.90%

29.10%

79.63%

20.37%

51.76%

48.24%

1,086

1,081

3,173

1,935

1,357

627

5,496

1,456

46,36910,21574,62030,62011,868

3,036

882

822

66.80%

33.20%

80.66%

19.34%

84.71%

15.29%

88.53%

11.47%

87.73%

12.27%

86.37%

13.63%

86.27%

13.73%

83.71%

16.29%

340

169

2,790

669

1,053

190

6,552

849

57,086

7,986

66,206

10,451

10,527

1,675

1,269

247

50.00%

50.00%

74.82%

25.18%

82.56%

17.44%

85.32%

14.68%

85.92%

14.08%

83.32%

16.68%

84.78%

15.22%

74.85%

25.15%

22

22

211

71

71

15

651

112

5,126

840

6,095

1,220

1,393

250

122

41

32.35%

67.65%

57.35%

42.65%

64.29%

35.71%

78.27%

21.73%

78.84%

21.16%

72.67%

27.33%

72.46%

27.54%

76.92%

23.08%

22

46

663

493

27

15

299

83

3,454

927

4,201

1,580

1,050

399

10

3

62.18%

37.82%

79.19%

20.81%

78.03%

21.97%

85.12%

14.88%

86.32%

13.68%

80.04%

19.96%

83.11%

16.89%

67.34%

32.66%

740

450

1,591

418

1,115

314

4,787

837

36,450

5,775

40,086

9,998

7,781

1,581

431

209

84.93%

15.07%

90.13%

9.87%

74.77%

25.23%

85.64%

14.36%

83.31%

16.69%

80.97%

19.03%

80.48%

19.52%

69.17%

30.83%

62

11

137

15

83

28

1,109

186

9,962

1,996

8,805

2,069

2,754

668

83

37

69.29%

30.71%

85.20%

14.80%

81.05%

18.95%

90.67%

9.33%

91.90%

8.10%

86.31%

13.69%

90.35%

9.65%

79.26%

20.74%

194

86

1,232

214

556

130

1,633

168

13,865

1,222

13,960

2,214

2,368

253

172

45

67.55%

32.45%

82.95%

17.05%

84.82%

15.18%

89.56%

10.44%

89.90%

10.10%

86.22%

13.78%

89.13%

10.87%

79.07%

20.93%

920

442

5,644

1,160

2,313

414

11,896

1,387

122,044

13,704

129,112

20,627

20,964

2,557

1,836

486

53.85%

46.15%

66.49%

33.51%

66.12%

33.88%

77.72%

22.28%

80.07%

19.93%

72.60%

27.40%

76.46%

23.54%

52.47%

47.53%

595

510

1,673

843

1,081

554

5,521

1,583

37,654

9,370

41,65015,717

8,577

2,640

489

443

58.82%

41.18%

59.33%

40.67%

67.50%

32.50%

56.43%

43.57%

64.28%

35.72%

66.06%

33.94%

58.02%

41.98%

56.98%

43.02%

50

35

213

146

54

26

1,022

789

9,370

5,207

9,384

4,821

1,920

1,389

49

37

39.02%

60.98%

46.92%

53.08%

55.57%

44.43%

62.36%

37.64%

65.51%

34.49%

55.18%

44.82%

61.86%

38.14%

42.36%

57.64%

787

1,230

2,337

2,644

883

706

2,944

1,777

29,532

15,55034,92428,370

7,165

4,417

352

479

62.78%

37.22%

74.86%

25.14%

80.17%

19.83%

87.03%

12.97%

88.79%

11.21%

80.89%

19.11%

85.62%

14.38%

68.63%

31.37%

823

488

3,663

1,230

1,799

445

5,757

858

60,8297,679

83,966

19,83912,101

2,032

1,015

464

67.18%

32.82%

81.15%

18.85%

86.35%

13.65%

89.16%

10.84%

89.37%

10.63%

85.70%

14.30%

88.18%

11.82%

78.81%

21.19%

436

213

2,144

498

1,120

177

4,253

517

37,027

4,402

54,289

9,056

7,700

1,032

900

242

52.17%

47.83%

56.06%

43.94%

61.22%

38.78%

62.54%

37.46%

67.74%

32.26%

64.10%

35.90%

64.66%

35.34%

52.62%

47.38%

3,284

3,011

9,689

7,595

3,830

2,426

18,148

10,870176,903

84,254

234,333

131,255

40,88922,348

1,707

1,537

47.36%

52.64%

53.92%

46.08%

59.62%

40.38%

63.49%

36.51%

67.38%

32.62%

60.52%

39.48%

63.06%

36.94%

54.29%

45.71%

323

359

1,631

1,394

508

344

3,289

1,891

26,096

12,631

27,581

17,993

5,543

3,247

171

144

37.60%

62.40%

37.44%

62.56%

44.19%

55.81%

37.18%

62.82%

41.32%

58.68%

50.17%

49.83%

44.61%

55.39%

42.37%

57.63%

47

78

243

406

95

120

667

1,127

7,217

10,250

6,689

6,643

2,152

2,672

25

34

39.80%

60.20%

47.50%

52.50%

53.61%

46.39%

63.61%

36.39%

70.98%

29.02%

60.08%

39.92%

68.67%

31.33%

43.69%

56.31%

466

705

1,766

1,952

617

534

2,447

1,400

27,992

11,44229,542

19,631

6,182

2,821

277

357

68.16%

31.84%

79.22%

20.78%

82.42%

17.58%

87.69%

12.31%

89.28%

10.72%

83.63%

16.37%

87.11%

12.89%

73.53%

26.47%

1,310

612

4,925

1,292

2,598

554

6,810

956

80,266

9,636

110,927

21,715

15,335

2,270

1,228

442

44.23%

55.77%

48.63%

51.37%

50.76%

49.24%

51.90%

48.10%

56.01%

43.99%

58.04%

41.96%

52.41%

47.59%

64.84%

35.16%

46

58

160

169

201

195

1,992

1,846

18,104

14,22011,379

8,225

3,166

2,875

59

32

52.82%

47.18%

66.04%

33.96%

69.84%

30.16%

62.41%

37.59%

63.02%

36.98%

69.62%

30.38%

64.85%

35.15%

63.99%

36.01%

159

142

558

287

359

155

4,072

2,453

38,25322,44730,68913,393

11,489

6,228

263

148

48.87%

51.13%

60.15%

39.85%

63.73%

36.27%

64.90%

35.10%

65.35%

34.65%

62.95%

37.05%

65.23%

34.77%

46.88%

53.13%

217

227

984

652

239

136

795

430

5,350

2,837

8,057

4,742

1,452

774

45

51

PAGE 160 The Researcher Journey Through a Gender Lens

TABLE B.1 (CON’T)

Country

Active authors during the periods 1999–2003

GenderNumber and percent of men and women among authors ineach country and the EU28 overall and in each subject area.
Spain

All
Agricultural Sciences
Arts and Humanities
BiochemistryBusiness
ChemicalEngineering
ChemistryComputer Science
Decision Sciences
Dentistry
Earth and Planetary
Sciences
Economics
EnergyEngineering
Environmental
Science
Health Professions
Immunology andMicrobiology
Materials Science
Mathematics
Medicine
Neuroscience
NursingPharmacology
Physics andAstronomy
Psychology
Social Sciences
Veterinary

FranceItaly% of authors

Subject Area

Netherlands

Germany

Denmark

Number of authors

Australia

Japan

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

64.62%

35.38%

67.23%

32.77%

62.23%

37.77%

80.17%

19.83%

79.51%

20.49%

75.77%

24.23%

70.55%

29.45%

89.87%

10.13%

50,05427,40189,05843,404

68,821

41,76534,8808,630

129,71733,437

12,175

3,893

35,46514,806

209,979

23,67158.09%

41.91%

62.46%

37.54%

56.59%

43.41%

79.21%

20.79%

71.29%

28.71%

72.19%

27.81%

74.27%

25.73%

85.95%

14.05%

5,574

4,022

8,633

5,188

5,019

3,850

3,639

955

9,482

3,818

1,763

679

6,310

2,186

13,9032,273

67.85%

32.15%

65.32%

34.68%

58.65%

41.35%

76.93%

23.07%

74.88%

25.12%

72.93%

27.07%

61.39%

38.61%

86.99%

13.01%

859

407

1,844

979

919

648

1,044

313

2,054

689

264

98

1,180

742

903

135

52.90%

47.10%

54.16%

45.84%

48.25%

51.75%

73.04%

26.96%

68.19%

31.81%

70.28%

29.72%

63.53%

36.47%

85.20%

14.80%

9,463

8,424

20,59017,42915,02916,119

8,335

3,077

28,535

13,309

3,311

1,400

7,085

4,068

56,2759,776

71.37%

28.63%

75.57%

24.43%

72.22%

27.78%

85.42%

14.58%

87.26%

12.74%

85.66%

14.34%

70.49%

29.51%

85.26%

14.74%

648

260

857

277

468

180

861

147

1,610

235

239

40

1,302

545

810

140

61.09%

38.91%

69.10%

30.90%

64.65%

35.35%

86.41%

13.59%

84.13%

15.87%

81.79%

18.21%

82.96%

17.04%

91.00%

9.00%

2,434

1,550

4,687

2,096

2,270

1,241

1,908

300

8,321

1,570

530

118

1,305

268

12,4341,230

57.58%

42.42%

67.65%

32.35%

59.55%

40.45%

85.71%

14.29%

82.39%

17.61%

77.36%

22.64%

80.87%

19.13%

89.45%

10.55%

5,897

4,344

11,737

5,613

6,160

4,184

3,467

578

18,047

3,858

1,189

348

2,807

664

30,803

3,633

80.99%

19.01%

83.31%

16.69%

79.31%

20.69%

90.68%

9.32%

92.21%

7.79%

91.59%

8.41%

85.70%

14.30%

95.67%

4.33%

4,981

1,169

10,238

2,051

6,079

1,586

3,456

355

14,032

1,185

948

87

3,501

584

17,958813

73.74%

26.26%

80.64%

19.36%

71.38%

28.62%

90.67%

9.33%

90.70%

9.30%

90.12%

9.88%

83.09%

16.91%

94.27%

5.73%

483

172

779

187

459

184

544

56

1,014

104

146

16

516

105

543

33

68.15%

31.85%

72.83%

27.17%

74.31%

25.69%

83.79%

16.21%

80.41%

19.59%

69.35%

30.65%

77.03%

22.97%

87.79%

12.21%

336

157

260

97

483

167

274

53

788

192

86

38

228

68

2,394

333

74.68%

25.32%

77.03%

22.97%

72.87%

27.13%

88.78%

11.22%

85.82%

14.18%

86.06%

13.94%

84.04%

15.96%

94.27%

5.73%

2,726

924

6,939

2,069

4,582

1,706

2,359

298

7,992

1,321

846

137

3,312

629

7,306

444

74.06%

25.94%

76.41%

23.59%

75.67%

24.33%

90.81%

9.19%

87.13%

12.87%

87.55%

12.45%

81.75%

18.25%

94.82%

5.18%

728

255

1,027

317

650

209

771

78

1,158

171

232

33

887

198

476

26

77.35%

22.65%

82.48%

17.52%

83.23%

16.77%

91.98%

8.02%

92.66%

7.34%

88.63%

11.37%

90.72%

9.28%

96.61%

3.39%

915

268

2,185

464

1,290

260

700

61

3,066

243

265

34

616

63

7,458

262

78.86%

21.14%

82.78%

17.22%

80.59%

19.41%

92.94%

7.06%

91.63%

8.37%

90.14%

9.86%

88.11%

11.89%

96.23%

3.77%

7,007

1,878

20,275

4,219

11,928

2,873

6,449

490

30,891

2,822

1,646

180

5,348

722

57,7702,26462.86%

37.14%

68.81%

31.19%

64.14%

35.86%

85.00%

15.00%

80.60%

19.40%

76.61%

23.39%

77.12%

22.88%

89.94%

10.06%

2,941

1,738

4,923

2,231

3,130

1,750

2,822

498

8,258

1,988

1,176

359

3,758

1,115

7,643

855

62.86%

37.14%

64.74%

35.26%

63.40%

36.60%

76.00%

24.00%

75.64%

24.36%

74.27%

25.73%

56.99%

43.01%

86.22%

13.78%

462

273

1,219

664

920

531

624

197

2,009

647

179

62

901

680

1,690

270

49.91%

50.09%

48.24%

51.76%

43.23%

56.77%

68.54%

31.46%

62.23%

37.77%

66.56%

33.44%

61.04%

38.96%

83.12%

16.88%

2,779

2,789

5,185

5,563

3,261

4,283

2,697

1,238

6,724

4,081

1,047

526

2,167

1,383

11,321

2,299

69.44%

30.56%

77.69%

22.31%

72.11%

27.89%

91.20%

8.80%

88.72%

11.28%

88.81%

11.19%

85.90%

14.10%

94.86%

5.14%

4,545

2,000

14,608

4,194

6,578

2,544

3,815

368

22,959

2,920

897

113

3,077

505

42,4762,300

80.83%

19.17%

83.51%

16.49%

75.39%

24.61%

91.41%

8.59%

91.45%

8.55%

93.06%

6.94%

88.15%

11.85%

95.11%

4.89%

4,677

1,109

9,404

1,857

5,079

1,658

2,619

246

11,862

1,109

832

62

2,396

322

10,319530

62.52%

37.48%

58.88%

41.12%

57.64%

42.36%

73.66%

26.34%

72.98%

27.02%

69.72%

30.28%

62.07%

37.93%

87.02%

12.98%

22,828

13,68527,87919,47233,31524,481

14,066

5,030

42,482

15,725

4,836

2,100

12,4507,608

79,152

11,80653.91%

46.09%

54.52%

45.48%

49.66%

50.34%

72.58%

27.42%

69.35%

30.65%

70.57%

29.43%

62.66%

37.34%

84.13%

15.87%

1,684

1,440

3,660

3,053

3,494

3,542

1,609

608

6,703

2,963

494

206

1,490

888

9,189

1,734

49.56%

50.44%

46.85%

53.15%

52.08%

47.92%

64.44%

35.56%

66.58%

33.42%

56.58%

43.42%

36.79%

63.21%

75.21%

24.79%

558

568

639

725

762

701

453

250

1,020

512

159

122

596

1,024

1,089

359

50.14%

49.86%

55.94%

44.06%

48.19%

51.81%

74.15%

25.85%

70.41%

29.59%

68.00%

32.00%

64.12%

35.88%

84.11%

15.89%

2,334

2,321

4,311

3,396

3,283

3,530

1,664

580

5,408

2,273

576

271

1,149

643

15,3252,895

76.53%

23.47%

80.26%

19.74%

77.33%

22.67%

91.18%

8.82%

89.79%

10.21%

90.53%

9.47%

86.67%

13.33%

95.13%

4.87%

6,142

1,884

20,193

4,968

11,659

3,418

4,965

480

29,118

3,310

1,492

156

3,575

550

47,0632,408

58.10%

41.90%

55.73%

44.27%

48.55%

51.45%

70.25%

29.75%

67.11%

32.89%

64.06%

35.94%

52.27%

47.73%

77.15%

22.85%

875

631

1,279

1,016

788

835

1,197

507

2,208

1,082

123

69

1,139

1,040

878

260

69.18%

30.82%

67.55%

32.45%

63.96%

36.04%

78.82%

21.18%

79.51%

20.49%

76.81%

23.19%

61.43%

38.57%

87.28%

12.72%

1,598

712

2,920

1,403

1,441

812

2,475

665

4,178

1,077

616

186

3,321

2,085

2,148

313

55.84%

44.16%

60.03%

39.97%

57.98%

42.02%

76.04%

23.96%

65.09%

34.91%

65.88%

34.12%

67.23%

32.77%

84.06%

15.94%

641

507

787

524

654

474

546

172

1,225

657

278

144

595

290

1,872

355

Supplemental Data PAGE 161

TABLE B.2

Country

Average publication count of men and women who were actively publishingin any authorship position and as corresponding author, first author or lastauthor. Data provided for active authors in each country and the EU28.

GenderPosition

Average publication count

Average publication count during the period 2014–2018
Argentina
Men

BrazilWomen

Men

MexicoWomen

Men

Canada

Women

Men

USA

Women

Men

EU28

Women

Men

UK

Women

Men

Portugal

Women

Men

Women

Any

4.59

3.56

4.27

3.11

4.18

2.96

6.92

4.24

6.61

4.10

8.10

5.04

7.71

4.51

7.16

4.70

Corresponding

2.44

2.09

2.49

2.00

2.65

2.07

3.57

2.67

3.26

2.51

3.08

2.42

3.04

2.31

3.09

2.65

First

1.94

1.74

1.76

1.51

1.83

1.57

2.28

1.95

2.23

1.93

2.42

2.08

2.27

1.94

2.42

2.14

Last

2.89

2.52

3.12

2.65

2.42

1.89

4.52

2.91

3.98

2.69

4.17

2.89

4.10

2.80

4.38

3.24

Spain
Men

France

Women

Men

Italy

Women

Men

Netherlands

Women

Men

Women

GermanyMen

Denmark

Women

Men

Australia

Women

Men

Japan

Women

Men

Women

Any

6.67

4.48

8.28

5.23

10.60

6.85

8.70

5.56

8.16

4.54

8.59

4.91

8.28

5.09

5.92

3.29

Corresponding

3.03

2.35

2.86

2.23

3.67

2.85

3.09

2.60

3.07

2.36

3.12

2.45

3.57

2.77

3.11

2.06

First

2.48

2.09

2.31

1.94

3.03

2.44

2.39

2.32

2.32

1.90

2.45

2.07

2.56

2.22

2.16

1.64

Last

3.67

2.51

3.86

2.86

4.44

3.21

5.14

4.14

4.84

3.23

5.14

3.75

4.83

3.26

4.39

2.52

Average publication count during the period 1999–2003
Argentina

BrazilMexicoCanada

USA

EU28

UK

Portugal

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Any

5.318

4.168

5.296

3.729

5.238

3.732

7.108

4.409

7.400

4.773

7.873

5.035

7.730

4.761

6.469

4.580

Corresponding

2.825

2.276

2.734

2.119

2.930

2.294

3.757

2.718

3.585

2.752

3.449

2.563

3.609

2.643

3.118

2.428

First

2.037

1.852

2.013

1.700

2.108

1.783

2.263

1.895

2.313

1.959

2.484

2.099

2.323

1.974

2.371

2.129

Last

2.848

2.391

2.793

2.251

2.436

1.883

3.370

2.163

3.496

2.340

3.848

2.360

3.656

2.349

3.434

2.638

Men

Women

Men

Women

Men

Women

Men

Any

6.976

5.056

7.848

5.280

8.765

5.853

8.425

Corresponding

3.331

2.555

3.190

2.443

3.720

2.728

3.308

First

2.487

2.171

2.348

2.025

2.813

2.274

2.481

Last

3.480

2.391

3.819

2.586

3.645

2.271

4.592

Spain

FrancePAGE 162 The Researcher Journey Through a Gender Lens

Italy

Netherlands
Women

Germany

Denmark

Men

Women

Men

4.852

8.281

4.602

2.560

3.602

2.598

2.382

2.603

2.858

4.474

Australia

Japan

Women

Men

Women

Men

Women

7.930

4.831

7.249

4.586

7.547

4.494

3.334

2.499

3.592

2.633

3.296

2.248

2.025

2.365

2.109

2.317

2.015

2.547

1.927

2.405

3.819

2.409

3.287

2.232

4.597

2.693

TABLE B.3

Country

Average FWCI of women and men who were active
authors in the period 2014–2018 and 1999–2003. Data
provided for each country and the EU28.

GenderPosition

Average FWCI

Average FWCI 2014–2018
Argentina

BrazilWomen

Men

Canada

Any

0.658

0.630

0.619

0.619

0.580

0.579

1.194

1.173

1.388

1.354

Corresponding

0.579

0.547

0.602

0.564

0.482

0.477

1.009

0.965

1.100

1.025

First

0.694

0.672

0.679

0.646

0.580

0.592

1.270

1.131

1.485

1.278

Last

0.639

0.618

0.565

0.512

0.523

0.515

1.161

1.084

1.271

1.208

Italy

Men

Women

Netherlands

Men

EU28

Women

France

Women

USA

Men

Spain

Men

MexicoWomen

Germany
Men

Women

Men

UK

Portugal

Women

Men

Women

1.118

1.096

1.386

0.980

0.899

1.171

1.214

1.083

1.060

0.987

Denmark

Men

Women

1.452

0.903

0.898

1.128

0.860

0.807

1.529

1.408

1.006

0.917

1.311

1.343

0.892

0.799

Australia

Japan

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Any

0.936

0.925

1.055

1.059

1.124

1.082

1.432

1.403

1.172

1.197

1.364

1.356

1.232

1.232

0.720

0.699

Corresponding

0.831

0.788

0.918

0.808

0.989

0.915

1.260

1.229

1.001

0.933

1.256

1.165

1.109

1.083

0.639

0.571

First

1.030

0.961

1.138

1.048

1.188

1.086

1.523

1.359

1.279

1.166

1.468

1.263

1.371

1.251

0.758

0.683

Last

0.895

0.842

1.006

0.956

1.118

1.072

1.329

1.296

1.114

1.065

1.267

1.255

1.225

1.220

0.665

0.622

Average FWCI 1999–2003
Argentina

BrazilMexicoCanadaUSA

UK

Portugal

Men

Women

Men

Women

Men

Women

Men

Women

Women

Men

Women

Men

Women

Men

Women

Any

0.714

0.621

0.651

0.630

0.700

0.687

1.278

1.400

1.513

1.626

1.085

1.101

1.306

1.462

0.946

0.919

Corresponding

0.608

0.532

0.584

0.534

0.582

0.527

1.097

1.102

1.287

1.220

0.962

0.871

1.152

1.127

0.856

0.767

First

0.743

0.626

0.702

0.663

0.694

0.665

1.413

1.353

1.714

1.614

1.213

1.119

1.534

1.514

0.960

0.918

Last

0.666

0.630

0.646

0.592

0.624

0.634

1.333

1.347

1.558

1.603

1.098

1.032

1.376

1.515

0.898

0.890

Men

Women

Men

Women

Men

Women

Any

0.839

0.889

1.055

1.095

0.926

0.965

1.415

1.512

Corresponding

0.774

0.731

0.938

0.859

0.813

0.758

1.259

1.270

First

0.899

0.913

1.180

1.130

0.950

0.931

1.550

1.541

Last

0.830

0.811

1.073

1.079

0.922

0.901

1.371

1.405

Spain

France

Italy

Netherlands
Men

Women

Men

EU28

GermanyMen

Denmark

Women

Men

Women

1.159

1.267

1.424

1.391

0.994

0.919

1.246

1.229

1.279

1.248

1.563

1.373

1.165

1.187

1.387

1.353

Australia
Men

Japan

Women

Men

Women

1.150

1.233

0.826

0.851

1.026

1.006

0.692

0.567

1.336

1.236

0.869

0.798

1.248

1.236

0.788

0.714

Supplemental Data PAGE 163

TABLE B.4

Country

Average number of research grants won by women andmen during the period 2014–2018.
CanadaAverage number of
research grants won

USA

GenderAverage Award Count

EU28

Men

Women

Men

Women

3.623

2.535

3.428

3.083

Men

UK

Germany

Australia

Japan

Women

Men

Women

Men

Women

Men

Women

Men

Women

1.069

1.977

1.631

1.478

1.243

1.663

1.447

1.049

1.019

1.119

TABLE B.5

Country

Average number of patent applications by women andmen inventors and assignees in each country and the EU28
during the periods 2012–2016 and 1999–2003.

GenderPosition

Average number of patents

2012–2016
BrazilMen

Canada

Women

Men

USA

Women

Men

EU28

Women

Men

UK

Women

Men

Spain

Women

Men

France

Women

Men

Italy

Women

Men

Women

Inventor

3.57

3.06

5.45

4.43

6.31

4.54

7.06

5.68

6.72

5.70

3.93

3.58

7.06

6.01

5.41

5.02

Assignee

2.71

1.86

2.83

2.13

4.35

3.31

4.79

2.93

3.32

2.74

2.65

1.80

5.67

2.34

2.80

2.78

Women

Men

Women

Men

Netherlands
Men

Women

GermanyMen

Denmark

Women

Men

Australia

Women

Men

Japan

Women

Men

Women

Inventor

6.98

5.91

8.27

6.75

5.97

5.29

4.73

3.79

10.57

7.07

Assignee

7.18

2.34

5.73

4.07

3.26

2.16

2.85

1.99

10.04

4.64

Women

Men

Women

Men

1999–2003
BrazilMen

Canada

Women

Men

USA

Women

Men

EU28

UK

Spain

Women

Men

France

Italy
Women

Inventor

3.86

3.25

5.08

4.63

5.12

4.58

8.07

7.17

6.70

6.17

5.33

5.52

7.75

7.36

7.26

7.74

Assignee

2.55

1.37

2.45

1.96

4.44

2.98

4.52

2.37

2.60

1.97

2.73

1.89

4.05

2.22

2.96

2.59

Netherlands
Men

Women

GermanyMen

Denmark

Women

Men

Australia

Women

Men

Japan

Women

Men

Women

Inventor

6.23

5.41

9.48

8.31

7.21

6.86

4.81

6.31

8.79

5.90

Assignee

6.60

1.73

5.87

2.96

2.80

2.00

2.29

5.92

7.98

3.30

PAGE 164 The Researcher Journey Through a Gender Lens

TABLE B.6

Statistics on cohorts of authors whose first publication was in 2009 andwho published again at least once in any year up to 2018. Decline in authors(count and percent decline) during the period 2010–2018 is shown.
Argentina
Men

Australia
Men

Women

Men

1,191

4,227

3,161

9,185

-80

-94

-311

-250

-7.24

-7.89

-7.36

-7.91

Number of Authors
in Year 2

1,105

Decrease in Authors
Per Year
Percent Decrease

Women

BrazilCanadaWomen

Germany

Denmark

Men

Women

Men

Women

Men

7,181

6,838

4,239

15,618

7,730

1,356

-749

-624

-564

-374

-1,330

-721

-8.15

-8.69

-8.25

-8.82

-8.52

-9.33

Difference inPercent Decrease

0.65

Difference

10%

4%

3%

N

808

2,653

4878

0.55

0.53

0.57

Spain

Women

EU28

Men

Women

Men

Women

764

6,884

5,748

72,26948,250

-97

-63

-533

-464

-5,711-4,041

-7.15

-8.25

-7.74

-8.07

-7.9

-8.38

0.81

1.09

0.33

0.47

4%

6%

9%

3%

4%

3232

6513

777

4281

39373

DF

1

1

1

1

1

1

1

1

X2

8.93

4.396

5.073

5.638

23.235

5.686

4.23

67.013P

0.00280.036

0.02430.0176<0.0001

0.01710.0397<0.0001

France

UK

Italy

Japan

MexicoNetherlands

Portugal

USA

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Men

Women

Number of Authors
in Year 2

8,737

5,929

11,222

6,912

6,653

6,127

19,905

3,765

2,373

1,400

3,682

1,855

1,406

1,288

51,333

26,443

Decrease in Authors
Per Year

-694

-593

-874

-586

-483

-484

-1,833

-371

-182

-114

-287

-153

-104

-94

-4,485-2,399Percent Decrease

-7.94

-10

-7.79

-8.48

-7.26

-7.9

-9.21

-9.85

-7.67

-8.14

-7.79

-8.25

-7.4

-7.3

-8.74

-9.07

Difference inPercent Decrease

2.06

0.69

0.64

0.65

0.47

0.45

0.1

0.34

Difference

4%

6%

5%

4%

3%

3%

1%

3%

N

4755

5935

4710

4973

1243

1892

1013

20374

DF

1

1

1

1

1

1

1

1

X2

8.063

21.61712.515

5.52

1.15

1.637

0.108

20.62

P

0.0045<0.0001

0.00040.02

0.28360.20080.7426<0.0001

Supplemental Data PAGE 165

Appendix C

Elsevier’s 2019 Researcher
Survey Results
FIGURE C.1

C.1

Summary of survey
responses to the question,“Why do you think there isa lack of gender balance inyour field?”
Responses were collected from948 researchers, including 338
women and 594 men. Results
were disaggregated by genderand responses were weighted tobe representative of the global
researcher population by country(UNESCO 2014 data). A check
mark indicates that the difference
was statistically significant basedon Z-test of proportion and that
we can be 90% confident thedifference is explained by gender(p < 0.10).

Percent

✓

0

10

20

30

40

Lack of diverse representation

80

90

100

50

60

70

80

90

100

24%

to potential recruits

18%

Lack of encouragement topursue education/careers in myfield from an early age

38%
36%

26%

and

19%

Bias or discrimination

38%✓ in recruitment, hiring and13%

promotion processes

C.2

70

25%

✓ in my field is off-putting

diversity plans

60

42%

The workplace culture is genderbiased✓ Insufficient inclusion

50

Percent

0

10

20

30

40

Women
Men

FIGURE C.2

Summary of survey
responses to the question,“Do you feel the proportion[of women to men in yourfield] has changed over the
past 10 years?”
Responses were collected from863 researchers, including 299
women and 551 men. Results
were disaggregated by genderand responses were weighted tobe representative of the global
researcher population by country(UNESCO 2014 data). Those who
responded “Don’t know” were
excluded from the analysis. A check
mark indicates that the difference
was statistically significant based on
Z-test of proportion and that we canbe 90% confident the difference is
explained by gender (p < 0.10).

PAGE 166 The Researcher Journey Through a Gender Lens

37%
More men now

Percent01061%More women now

20

30

40

50

80

90

100

80

90

100

3%

No, I feel the proportion has

43%✓ remained the same over31%

the past 10 years

52%

Yes, there are more
women now

66%
Percent

Men

70

5%

Yes, there are moremen now

Women

60

0

10

20

30

40

50

60

70

FIGURE C.3

Self-identified subject
area and gender of survey
respondents.

Life Sciences - 19%
Physical Sciences - 52%

Men

Social Sciences - 14%

WomenHealth Sciences - 14%

Percent

0

10

20

30

40

50

60

70

80

90

100

Medicine & Allied Health

41%

59%

Nursing83%

17%

Dentistry

20%

80%

Veterinarian Medicine/Science

46%

54%

Agriculture

41%

49%

Biochemistry, Genetics & Molecular Biology

27%

73%

Biological Sciences

41%

59%

Immunology & Microbiology

32%

68%

Neuroscience

53%

47%

Pharmacology, Toxicology & Pharmaceutics

44%

56%

Astronomy

13%

88%

Chemical Engineering

26%

74%

Chemistry

30%

70%

Computer Science/IT

30%

70%

Earth & Planetary Sciences

20%

80%

Electrical/Electronic Engineering

8%

92%

Engineering and Technology

14%

86%

Environmental Sciences

35%

65%

Material Science

22%

78%

Mathematics

21%

79%

Physics

17%83%

Arts & Humanities

70%

30%

Economics

31%

69%

Social Sciences

46%

54%

Psychology

65%

35%

Percent

0

10

20

30

40

50

60

70

80

90

43%
57%

40%
60%

21%
79%

50%
50%

100

Elsevier’s 2019 Researcher Survey Results PAGE 167

FIGURE C.4

C.4
Summary of survey

responses to thequestion, “Approximately
how many times in thepast year have you been
invited to collaborate
on a research projectthat could lead to a
publication?”. (Top)
Summary of survey
responses to thequestion, “Have you
had the opportunity to
be the coordinator Mean
of a
3.04
✓
collaborative research
3.52
project in the last year?”.
t=2.319(Bottom)
Responses collected from 1212
researchers, including 417
women and 773 men (Top) and
1153 researchers, including 401
women and 733 men. (Bottom)
Results were disaggregated bygender and responses were
weighted to be representative of
the global researcher populationby country (UNESCO 2014 data).
A check mark indicatesC.4
that
the difference was statisticallysignificant based on t-test andwe can be 90% confident thedifference is explained by gender(t > 1.645).

Number of times in the past year, I have been invited to collaborate
Percent

10

20

30

40

0

10
39%

Percent

80

90

100

20

30

40

50

60

70

80

9

50

60

70

80

9

80

90

100

100

80

9

11%

36%

Zero times

10%
39%

C.4

11+ times

70

42%

1 to 2 times

6 to 10 times

60

10%

C.4

3 to 5 times

50

11%

Zero times

42%

8%

1 to 2 times

Percent

9%

0

10

20

30

40
39%

11%

Zero times2%
3 to 5 times

36%

10%

39%

4%
Percent
0
1 to 2 times

10

6 to 10 times

20

408%

30

50

60

70

42%

39%

9%

Mean

✓

3.04
3.52
t=2.319

Zero times

Percent

36%

2%

3 to 5 times
11+ times
0

10

20

6 to 10 times

30

4%40

15% Percent 0

8%
10

13%

9%

50

60

70

39%

80

90

20

30

40

50

60

70

Mean
Numberof times in the past year, I have invited a collaborator to collaborate

✓

3.04

2 times
1 to
3.52
t=2.319

Women
Men

0

Percent

45%

2%

11+ times
0

20 Percent 300

10

11%

Zero
times
3 to 5 times

Zero times

times
to 210times
61 to

1 to 2 times

5 times
3 to times
11+

Zero times 2%
3 to 5 times

Percent

4%4010 44%5020

6030

7040

8050

9060

10070

80

9

15%20

30

40

50

60

70

80

9

44%50

60

70

80

9

45%
80

90

100

80

9

80

9

0
29%

10%

10

13%

32%

45%

42%

8%
Percent

7%

0

10
39%

20

30

40

Mean

✓

2.74
3.29

Percent

Mean

✓

3.04

39%

3%

t=2.039

6 to 10 times

36%

0

1 to 2 times
6 to 10 times

10
8%

20

30

40

8%

9%

15%

29%

13%

32%

50

60

70

44%

7%

Mean

✓

2.74

3.52

times
11+3.29t=2.319t=2.039

3 to 5 times2%
11+ times

4%

Percent

0

6 to 10 times

29%

2%

32%

3%
10

408%
10

20 Percent 300

5020

6030

7040

8050

9060

10070

100

7%

Mean

✓

2.74
3.29
t=2.039

Zero times

11+ times

Percent

0

2%
10

20

30

3% 40

50

60

70

80

90

15% Percent 0

10

20

30

40

50

60

13%

PAGE 168 The Researcher Journey Through a Gender Lens

45%

70

FIGURE C.5

C.5

Summary of survey
responses to thequestion, “How much do
C.5withyou agree/disagree
the below statements?”
with possible responses
being: “Strongly
disagree,” “Disagree,”“Neutral,” “Agree,”“Strongly agree” and“Don’t know.” Responses
were collected from 380
women and 685 men.
Results were disaggregated bygender and responses were
weighted to be representative of
the global researcher populationby country (UNESCO 2014data). Those who responded“Don’t know” were excluded
from the analysis. A check markindicates that the difference wasstatistically significant based on
Z-test of proportion and that
we can be 90% confident thedifference is explained by gender(p < 0.10).

Do you intend to change your job/workplace?
Percent

0

10

20

30

40

I intend to look for a
new job in the near future(% strongly agree + agree)

50

60

70

80

90

100

50

60

70

80

90

100

35%
37%
Percent

0

10

I would be happy to remain at mycurrenta I amto look foruntil
I intendworkplace
eligible/electretirefuture(% strongly
new job in thetonear
disagree+ disagree)
agree + agree)(% strongly

30

40

22%

35%

20%

II am
activelylookingforwould
be happy
to remainat myanotherjob (% strongly
current workplace
until I am
agree+
agree)
eligible/elect to retire (% strongly

37%

21%
22%
24%
20%

disagree + disagree)

Percent

20

0

10

20

I am actively looking foranother job (% strongly
agree + agree)

30

40

50

60

70

80

90

100

30
30

40
40

50
50

60
60

70
70

80
80

90
90

100
100

40

50

60

70

80

90

100

60

70

80

90

100

60

70

80

90

100

21%
24%
Percent
Percent

0
0

10
10

20
20

At any point as an active researcher have you contemplated changing career?
31%

Yes, to pursue a careeroutside of research

30%
Percent

0

10

20

30

23%

other reasons
forpursue
Yes, to✓ Yes,
a career18%

outside of research

31%
30%
47%

23%

No

✓ Yes, for other reasons

52%

18%
Percent

0

10

20

30

40

50

47%

No

52%

Women
Men

Percent

0

10

20

30

40

50

Elsevier’s 2019 Researcher Survey Results PAGE 169

C.5a
FIGURE C.5 (CON’T)

Why have you contemplated changing careers?

C.5a

Summary of survey
responses to thequestion, “How much do
you agree/disagree withthe below statements?”
with possible responses
being: “Strongly
disagree,” “Disagree,”“Neutral,” “Agree,”“Strongly agree” and“Don’t know.” Responses
were collected from 380
women and 685 men.
Results were disaggregated bygender and responses were
weighted to be representative of
the global researcher populationby country (UNESCO 2014data). Those who responded“Don’t know” were excluded
from the analysis. A check markindicates that the difference wasstatistically significant based on
Z-test of proportion and that
we can be 90% confident thedifference is explained by gender(p < 0.10).

Women
Men

Percent

0

10

20

30

40

50

70

80

90

100

60

70

80

90

100

45%

For a change/challenge/
exciting opportunity

46%

31%

✓ For family commitments

22%

32%

✓ Career is too demanding

19%

42%

Pay is inadequate

46%

6%

Policy8%38%Lack of career progression

34%

33%

✓ Job security

26%

20%

Experienced harassment✓ at work

✓

60

10%

18%

Experienced discrimination
at work

9%

8%

Other

6%

0%

✓ Don't know

4%
Percent

PAGE 170 The Researcher Journey Through a Gender Lens

0

10

20

30

40

50

FIGURE C.6

C.6

Summary of survey
responses to thestatement “I amconsidering moving
to another country tofurther my career in
research.” The figure
shows the gender
distribution of those
respondents who agreed
with the statement.

Percent

10

20

30

40

50

10

20

30

40

50

Overall
APAC
Eastern Europe
Latin America
North America
West Europe
Percent

Responses were collected from432 researchers. Results weredisaggregated by gender andresponses were weighted tobe representative of the global
researcher population by country(UNESCO 2014 data).

Women
Men

Elsevier’s 2019 Researcher Survey Results PAGE 171

FIGURE C.7

C.7

Summary of survey
results to a question
about who researchers“know,” where “knowing”
was defined as being
able to remember thename of the person (jobholder) and easily starta conversation when
encountering them. The
question was worded,“Do you know anyone
who is a/an/at [thisposition]?” with possible
responses being: “No,”“Yes, as an acquaintance,”“Yes, as a close friend”
and “Yes, as a close family
member.”Results shown here are based on
those respondents who indicatedknowing an individual in [thisposition] as a close friend or
family member. Responses werecollected from 1213 researchers,
including 417 women and 774
men. Results were disaggregatedby gender and responses were
weighted to be representative of
the global researcher populationby country (UNESCO 2014 data).
A check mark indicates thatthe difference was statisticallysignificant based on Z-test of
proportion and that we can be
90% confident the difference is
explained by gender (p < 0.10).

Women
Men

PAGE 172 The Researcher Journey Through a Gender Lens

High prestige positions
Percent

0

10

20

30

40

50

60

70

80

90

100

40

50

60

70

80

90

100

5%

Member of Parliament /Government

7%

8%Manager of a Governmental
Organization

10%

26%

Director or Head of Department

29%

16%

CEO of a Company

17%

Head of a Guild / ResearchCouncil / Board memberof a funding body

9%
14%

26%

Accredited society member

29%

15%

Journal Editor in Chief

18%

2%

✓ Chancellor/Vice Chancellor

9%

19%

✓ Dean26%
Percent

0

10

20

30

FIGURE C.7 (CON’T)

Summary of survey
C.7a
results to a question
about who researchers“know,” where “knowing”
was defined as being
able to remember thename of the person (jobholder) and easily starta conversation when
encountering them. The
question was worded,“Do you know anyone
who is a/an/at [thisposition]?” with possible
responses being: “No,”“Yes, as an acquaintance,”“Yes, as a close friend”
and “Yes, as a close family
member.”Results shown here are based on
those respondents who indicatedknowing an individual in [thisposition] as a close friend or
family member. Responses werecollected from 1213 researchers,
including 417 women and 774
men. Results were disaggregatedby gender and responses were
weighted to be representative of
the global researcher populationby country (UNESCO 2014 data).
A check mark indicates thatthe difference was statisticallysignificant based on Z-test of
proportion and that we can be
90% confident the difference is
explained by gender (p < 0.10).

Moderate prestige positions
Percent

0

10

20

30

40

50

60

70

80

90

100

90

100

34%

Head of Department

38%

78%

✓ Professor

73%
78%

✓ Senior Lecturer / Reader

73%

78%

/
✓ Lecturer, Assistant
Associate Professor

69%

74%

✓ Postdoctoral level of education

66%

83%

✓ Postgraduate level of education(Masters / PhD)

71%
Percent

0

10

20

30

40

50

60

70

80

Women
Men

Elsevier’s 2019 Researcher Survey Results PAGE 173

FIGURE C.8

Analysis of responses to a survey question about who researchers “know,” where“knowing” was defined as being able to remember the name of the person (jobholder) and easily start a conversation when encountering them. The question
was worded, “Do you know anyone who is a/an/at [this position]?” with possible
responses being: “No,” “Yes, as an acquaintance,” “Yes, as a close friend” and “Yes,as a close family member.”
Results shown here are based on those respondents who indicated knowing an individual in [this position]
as a close friend or family member. Responses were collected from 1213 researchers, including 417 womenand 774 men. Results were disaggregated by gender and responses were weighted to be representative of
the global researcher population by country (UNESCO 2014 data). The analysis was conducted for earlycareer researchers (ECR), defined as those who have been in research for up to 10 years, and late-career
researchers (LCR), defined as those who have more than 10 years of experience. A check mark indicates thatthe difference was statistically significant based on Z-test of proportion and that we can be 90% confident
the difference is explained by gender (p < 0.10).

C.8

Seniority differences by years in research
Percent

0

10

20

30

40

50

90

100

70

80

90

100

57%
59%
Percent

PAGE 174 The Researcher Journey Through a Gender Lens

80

49%

LCR

Men

70

38%

✓ ECR

Women

60

0

10

20

30

40

50

60

C.9

FIGURE C.9

Summary of survey
responses to thequestion, “Have you
had the opportunity to
be the coordinator of acollaborative research
project in the last year?”with possible responses
being: “Yes, and I
accepted the offer,” “Yes,and I declined the offer,”“No” and “Don’t know.”
Responses were collected from
1,153 researchers, including 401
women and 733 men. Results
were disaggregated by genderand responses were weighted tobe representative of the global
researcher population by country(UNESCO 2014 data). Those
who responded “Don’t know”
were excluded from the analysis.
A check mark indicates thatthe difference was statisticallysignificant based on Z-test of
proportion and that we can be
90% confident the difference is
explained by gender (p < 0.10).

No
45%

Yes, and I
accepted
the offer
50%

Yes, and I declined the offer
5%Strongly
Agree

65%

70%

20%

21%

45%

22%
Strongly
Disagree

11%

26%

70%

23%

49%

41%

47%

19%

23%

21%

10%

7%

7%

I find it easy to collaborate withcolleagues in my field of research✓

67%

The success of research is dependent on
greater collaboration outside of theimmediate research group/team

Women
Men

Elsevier’s 2019 Researcher Survey Results PAGE 175

C.10
FIGURE C.10

Summary of survey
responses to thequestion, “To what extent
do you agree or disagreewith the following
statements about yourwork environment?” withpossible responses being:“Strongly disagree,”“Disagree,” “Neutral,”“Agree,” “Strongly agree”
and “Don’t know.”
Responses were collected from
1,158–1,207 researchers, including
400–416 women and 737–769
men. Results were disaggregatedby gender and responses were
weighted to be representative of
the global researcher populationby country (UNESCO 2014 data).
Those who responded “Don’tknow” were excluded from theanalysis. (p < 0.10).

Percent strongly agree + agree

Men

PAGE 176 The Researcher Journey Through a Gender Lens

10

20

30

40

50

60

70

80

90

100

80

90

100

29%

To succeed you can't let familyinterfere with work

29%

24%

Taking days off is frowned upon

22%

People with significant demands
outside of work don't makeit very far

43%
42%

68%

To get ahead you need to beable to work long hours

72%

56%

Leadership expects employees
to put work first

59%

13%

Seeking other's advice isseen as weak

14%

25%

The most respected people
don't show emotions

Percent strongly agree + agree

Women

0

23%
0

10

20

30

40

50

60

70

C.11
FIGURE C.11

Summary of survey
responses to thequestion, “What doyou feel, if any, are thebiggest barriers to yourcareer progression?”
Responses were collected from1,213 researchers, including 417
women and 774 men. Results
were disaggregated by genderand responses were weighted tobe representative of the global
researcher population by country(UNESCO 2014 data). A check
mark indicates that the difference
was statistically significant basedon Z-test of proportion and that
we can be 90% confident thedifference is explained by gender(p < 0.10).

Women

Percent

0

10

20

30

Lack of sponsorship fromsenior colleagues

90

100

60

70

80

90

100

40%
38%

26%
20%

34%
29%

21%
25%

40%

Unable to take up development✓ opportunities because of other35%

commitments in the workplace45%✓ Balancing personal/private life

37%

10%

Other

8%

2%

Don't know / Prefer not to say

✓

80

10%

Lack of personal development
and training opportunities

Men

70

14%

Lack of opportunities in my field

✓

60

14%

✓ Harassment

I would need to relocate toprogress

50

18%✓ Discrimination

✓

40

3%

8%

I do not feel I will face any
barriers to my career progression

Percent

11%
0

10

20

30

40

50

Elsevier’s 2019 Researcher Survey Results PAGE 177

C.12
North America

FIGURE C.12

Summary of survey
responses to thequestion, “To what
extent do you agree
or disagree with thefollowing statements
about your job?” withpossible responses being:“Strongly disagree,”“Disagree,” “Neutral,”“Agree,” “Strongly agree”
and “Don’t know.”
Responses were collected from
400–416 women and 736–768
men. Results were disaggregatedby gender and region andresponses were weighted tobe representative of the global
researcher population by country(UNESCO 2014 data). Those
who responded “Don’t know”
were excluded from the analysis.
A check mark indicates thatthe difference was statisticallysignificant based on Z-test of
proportion and that we can be
90% confident the difference is
explained by gender (p < 0.10).

Percent strongly agree + agree

0

25

50

50

Asia

75

18%

20%

25%

41%

36%

43%

41%

72%

100

61%
74%

70%

41%

52%

65%

42%

48%

67%

5%

11%

19%

5%

13%

19%

27%

21%

18%
25

75

30%

62%

0

50

33%

70%

The most respected
people don’t show
emotions

25

24%

40%

Seeking other’s advice
is seen as weak

0

19%

47%

Leadership expects
employees to put work
first

100

31%

To get ahead you need
to be able to work long
hours

PAGE 178 The Researcher Journey Through a Gender Lens

25

23%

25%

People with significant
demands outside of work
don’t make it very far

Men

0

18%

Taking days off
is frowned upon

Women

100

22%

To succeed you can’t
let family interferewith work

Percent strongly agree + agree

Western Europe

75

23%
✓

14%
50

75

100

0

25

✓

50

75

100

29%
0

25

50

75

100

Appendix D

Authors and Contributors
Authors

Elsevier Contributors

Maria de Kleijn, MSc, MBA, Senior VicePresident, Analytical Services, Elsevier

Jeroen Baas, MSc, Director ProductManagement, Data Science, Elsevier

Bamini Jayabalasingham, PhD, Senior
Analytical Product Manager, Analytical
Services, Elsevier

Clive Bastin, PhD, Head of Program
Management, Analytical Services, Elsevier

Holly J. Falk-Krzesinski, PhD, Vice
President, Research Intelligence, Global
Strategic Networks, Elsevier
Tom Collins, MS, PhD, Data Scientist,
Research Products, Elsevier
Liliane Kuiper-Hoyng, MSc, Senior User
Researcher, Analytical Services, Elsevier
Isabella Cingolani, PhD, Analyst, Analytical
Services, Elsevier
Jin Zhang, MA, PhD, User Researcher,Analytical Services, Elsevier
Guillaume Roberge, MSc, Senior Research
Analyst, Science-Metrix, Elsevier
Gemma Deakin, Senior Research Manager,
Customer and Market Insights, Elsevier
Abigail Goodall, Research Executive,
Customer and Market Insights, Elsevier
Kjersten Bunker Whittington, PhD,
Associate Professor of Sociology, Reed
College
Stephane Berghmans, DVM, PhD, Vice
President, Academic & Research Relations
EU, Global Strategic Networks, Elsevier
Sarah Huggett, MA, Head of Analytical
Services APAC, Analytical Services, Elsevier
Stacey Tobin, PhD, The Tobin Touch
Authors contributed to the report as follows:

Conceptualization, M.dK., B.J., H.F-K. and S.B.;
Methodology, B.J., L.K-H., I.C., J.Z., G.R., G.D., A.G.,
K.B.W. and S.B.; Investigation, B.J., L.K-H., I.C., J.Z., G.R.,
G.D. and K.B.W.; Data Curation, B.J., T.C., L.K-H., I.C.,
G.R. and K.B.W.; Formal Analysis, B.J., L.K-H., I.C., J.Z.,
G.R., G.D., A.G and K.B.W.; Visualizations, B.J., L.K-H.,
I.C., G.R. and A.G.; Writing – Original Draft, B.J., L.K-H.,
I.C., J.Z., G.R., A.G., and S.H.; Writing - Final Review and
Edits, M.dK, B.J. and H.F-K.; Funding Acquisition, M.dK
and H.F-K.; Supervision, M.dK, B.J., H.F-K. and K.B.W.

Sacha Boucherie, MSc, Senior Manager
Communications, Global Communications,Elsevier
Yuhri Ishizaki, Global Strategic Networks
Associate APAC, Global Strategic Networks,
Elsevier
Anders Karlsson, PhD, Vice President,
Academic Relations (Japan APAC), Global
Strategic Networks, Elsevier
Marianne Parkhill, MS, Director, Content
and Engagement Marketing Strategy
Taylor Stang, MBA, Engagement Strategy
and Planning Director, Research Marketing,
Elsevier
Lesley Thompson, PhD, Vice President,
Academic and Government Strategic
Alliance, Global Strategic Networks, Elsevier

Susanna Chiocca, PhD, Director of viruses
and cancer unit IEO, Istituto European di
Oncologia; Member of Italian Ministryof Health working group on gender
medicine, Director of the Women in science
programme at IEO; EU-LIFE Gender
Equality Working Group
Mary Frank Fox, PhD, Professor, Schoolof Public Policy, Georgia Institute ofTechnology
Gabriel O’Riordain, PhD, CeMM - ResearchCenter for Molecular Medicine of theAustrian Academy of Sciences; EU-LIFE
Gender Equality Working GroupEleni Papadimitriou, MSc, Scientific
Officer, Joint Research Centre, European
Commission
Sonja Reiland, PhD, Project Manager andMember, CRG Gender Balance Committee,
Centre for Genomic Regulation; ProjectManager of LIBRA, H2020 project ongender equality in science; EU-LIFE Gender
Equality Working Group

Daniella Voermans, MSc, Program
Manager, Analytical Services, Elsevier

Cheryl Smythe, PhD, International Grant
Manager, Babraham Institute, EU-LIFE
Gender Equality Working Group

Subject Matter Expert
Contributors

Alice Szczepanikova, MPhil, PhD, Scientific
Officer, Joint Research Centre, European
Commission

Sandra W. Robert, CAE, CEO, Association
for Women in Science (AWIS) –Interviewee
Sarah Sharples, CErgHF, FIET, FIEHF,
PhD, MSc, BSc (hons), PGCAP, Pro-ViceChancellor for Equality, Diversity andInclusion, University of Nottingham –Interviewee
Charlina Vitcheva, MA, MS, Acting
Director-General, Joint Research Centre,
European Commission – Interviewee
Miyoko O. Watanabe, PhD, Deputy
Executive Director, and Director, Office forDiversity and Inclusion, Japan Science andTechnology Agency (JST) – Interviewee
Marta Agostinho, PhD, EU-LIFE
Coordinator; EU-LIFE Gender Equality
Working Group

Henri Van Luenen, PhD, Director ofOperations, NKI, The Netherlands Cancer
Institute; EU-LIFE Gender Equality Working
Group
Isabella Vernos, PhD, ICREA Research
Professor; Chair of the CRG Gender
Balance Committee Coordinator of LIBRA;
Former chair of the ERC Gender Balance
Working Group; EU-LIFE Gender Equality
Working Group

This report was designed for print
and online by Sandstorm®
(www.sandstormdesign.com)

Pernille Brandt, Cand Jur, LLM, Strategic
HR Projects, Joint Research Centre,
European Commission

Authors and Contributors PAGE 179

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