Gender differences in scientific productivity: a persisting phenomenon?
P. van den Besselaar (&) Department of Organization Science & Network Institute, VU University Amsterdam
Amsterdam, The Netherlands
I. van der Weijden CWTS,
Leiden, The Netherlands
P. van Arensbergen Science System Assessment, Rathenau Institute
, The Hague,
There is substantial literature on research performance differences between male and female researchers, and its explanation. Using publication records of 852 social scientists, we show that performance differences indeed exist. However, our case study suggests that in the younger generation of researchers these have disappeared. If performance differences exist at all in our case, young female researchers outperform young male researchers. The trend in developed societies, that women increasingly outperform men in all levels of education, is also becoming effective in the science system.
The academic world has been dominated by men for a long time. However, the share of
women in academia is gradually increasing. Worldwide female students nowadays even
outnumber male students, with 55 % in the UK and USA and with 59 % in the
Scandinavian countries (OECD 2010). And of the new entrance in European higher education
about 55 % is female.1 Figure 1 shows the percentage of women in different academic
positions in the Netherlands. There, the position of women in higher academic positions is
even lower than elsewhere. The growing share of women is characteristic for all positions,
1 Of course this differs between the various fields of study. In most science, technology and engineering
fields, the share of women is low.
Fig. 1 Share of women
in academic positions the
PhD Other Assistant Associate Full
students academic professors professors professors
however the general rule still is the higher the rank in academia, the lower the number of
women (Brouns 2000; De Weert 2001; Timmers et al. 2010). Although female researchers
are improving their position, the process is rather slow. Is the weak position due to women
having in average fewer ambitions in pursuing an academic career? Are career decisions
characterized by gendered social closure, structurally disadvantaging women? Or are
women weakly represented in high ranks because their male colleagues outperform them?
In this paper we will address the last question by focusing on differences in research
performance between male and female researchers.
Ample evidence has been provided for a productivity difference between men and
women over time, with men producing more research output than women (Cole and
Zuckerman 1984; Long 1992; Xie and Shauman 1998; Nakhaie 2002; Prpic 2002; Penas
and Willett 2006; Symonds et al. 2006; Taylor et al. 2006; Ledin et al. 2007; Abramo et al.
2009). However, with regard to citations per publication no gender differences were found
(Penas and Willett 2006; Ledin et al. 2007; Tower et al. 2007), or even a difference in the
opposite direction; women having a higher citation score than men (Long 1992; Powell
et al. 2009). The lower research productivity of women implies that female researchers
receive in average a lower total number of citations than men do.
Zuckerman (2001) suggest four different types of explanations of the productivity
puzzle (Cole and Zuckerman 1984): scientific ability, self-selection, social selection, and
accumulated disadvantage. According to the scientific ability explanation, male and female
academics have different biological and psychological characteristics that directly affect
the research output. However, no direct gender effect has been found in earlier research
(e.g. Xie and Shauman 1998).
The self-selection explanation argues that scientific productivity is influenced by the
individual choices of the academics themselves. Several studies confirm the influence of
individual choices. For example, women more often interrupt their career to have children
and start a family (Prozesky 2008). Having children causes a decline in research
productivity growth, more for women than for men (Fuchs et al. 2001; Hunter and Leahey
2010). Women were also found to initiate their careers at a later age than men
(Karamessini 2004; Prozesky 2008). This also holds for their publication career: women produce
fewer publications than men during the first decade of their career (Long 1992; Symonds
et al. 2006), but later in their career they more or less catch up with male researchers (Long
1992; Symonds et al. 2006). Other factors which are found to affect research productivity
and can be considered as self-selection are marital status,2 career ambitions, amount of
2 Other evidence suggests that the effect of marital status is less univocal (Fox 2005).
research time, degree of specialization, discipline, reputation of the university and
department, international network (collaboration and co-authoring), and academic rank
(Allison and Long 1990; McNamee et al. 1990; Dundar and Lewis 1998; Prpic 2002; Lee
and Bozeman 2005; Bland et al. 2006; Carayol and Matt 2006; Leahey 2006; Taylor et al.
2006; Puuska 2010). Many of these factors have a gender dimension, as women in average
work at lower ranks, in less prestigious institutions, have in average less experience and a
weaker (inter)national network. They also specialize less (Leahey 2006) and more often
concentrate on teaching and service, and therefore spend less time on research (Taylor
et al. 2006; Snell et al. 2009). However one should recognize that these factors cannot
always be fully ascribed to self-selection. For example, decisions related to collaboration
and academic rank are partly in the hands of other people and the organization of the
Zuckermans third type of explanation, social selection, outlines how research
productivity of women is affected by gender-based decisions made by others (Zuckerman
2001). Just as in society in general, there may exist mechanisms of discrimination in the
social organization of science (Prpic 2002). Men outnumber women in positions of formal
power, authority and high income (Xie and Shauman 1998; Timmers et al. 2010). Research
on professorial appointments shows there are gender differences in the selection and
recruitment procedures. A clear disparity was found in the success rates of male and female
applicants to the disadvantage of females (Van den Brink et al. 2006). This implies that
career decisions are characterized by gendered social closure (Van den Brink 2009).
A similar situation has been observed in the procedures of grant allocation. Quite some
research has focused on gendered aspects of peer review, especially since Wenneras and
Wold (1997) published their study on nepotism and sexism in science. They showed that
women needed a higher performance to be as successful as male researchers. And,
researchers without committee members in their network needed much higher performance
than those with an adequate network. A similar study on grant applications in the
Netherlands confirmed that gender matters (Brouns 2000). However, it showed that the way it
matters varies for different disciplines. Whereas in some disciplines in case of equal
average publication scores more men than women were evaluated as excellent, less
productive women also obtained grants in other disciplines. Replicating the study of Wenneras
and Wold 10 years later, Sandstrom and Hallsten (2008) found no sexism anymore; female
researchers even had a slightly better chance than males. Clearly, the council studied in
both papers changed its policy in the meantime. However, nepotism was as strong as
before. If that is the case, this may still influence female researchers, as male researchers
generally have better networks than female researchers (Kyvik and Teigen 1996; Fuchs
et al. 2001) and collaboration influences performance (Lee and Bozeman 2005).
Furthermore, women receive less academic support and mentoring than men (Landino and Owen
1988; Fuchs et al. 2001). This may be a disadvantage for women too, as academic careers
depend on support by academic mentors (Van Balen 2010).
The factors described above may overlap, and constitute the source of other events
influencing research productivity. For example status in science can be both the cause and
effect of scientific collaboration. The same holds for the relation between scientific status
and publication productivity (Fox 2005). The accumulation of decisions or events over
time generally placing women at a disadvantage is called cumulative disadvantage
(Zuckerman 2001). However, if productivity differences relate to individual (often
gendered) factors, such as ambition, focus on research, and changing gender roles and
responsibilities in family life (Xie and Shauman 1998; Taylor et al. 2006; Prozesky 2008),
one may expect that gradually changing gender roles in the last decades may have resulted
into changed behavior.
In a recent review, (Ceci and Williams 2011) discuss the evidence about discrimination
against women in science, in journal reviewing, grant funding, and in hiring. They suggest
that no evidence is available that supports the current discrimination against women in
science. As a consequence, the unequal position of women in science would be based on
quality differences between male and female researchers that may partly be based on free
choices, and partly on discriminatory arrangements in society at largee.g., inequalities
related to division of domestic work and child care. If this is correct, a careful analysis of
these performance differences between male and female researchers is
necessaryespecially an analysis of changes in performance differences over time. We would actually
expect changes, as women increasingly perform better at all levels in the educational
system (Buchmann et al. 2008; Pekkarinen 2008).
In this study, we answer the question of whether the gendered productivity differences are
persistent or whether they change over time. As it was suggested that the productivity gap
occurs in the early career (Symonds et al. 2006), we especially focus on the gendered
performance differences among the youngest generation. Research performance in this
paper is defined in terms of productivity (number of publications), and in terms of impact
(number of citations).
Materials and methods
Comparing male and female researchers requires a good identification of the population.
We use data on research grant applications in the Netherlands to analyze productivity
differences. The dataset3 covers about 1,100 applications, in a 3 years period, covering
three programs: early (ECG) and advanced career grants (ACG), and an open competition
scheme (OC), all within the social sciences.
The young career grant scheme is meant for researchers who got a Ph.D. within the
previous 3 years. The grant allows them to continue to develop their ideas further.
The advanced career scheme is for senior researchers with a long (up to 15 years)
post-doctoral experience, and who have shown the ability to successfully develop
their own innovative lines of research and to act as coaches for young researchers.
The grant allows them to build their own research group.
The open competition is for professors and senior researchers. They can apply for a
4-year full-time Ph.D. research project or a 3-year full-time postdoc project.
This set of applicants can be considered as a good representation of active social science
researchers, as active researchers are expected to apply regularly in these programs.
3 The data were prepared in the context of a previous project (Van den Besselaar and Leydesdorff 2009;
Bornmann et al. 2010). Coupling between publication and citation data with project data was based on name
and first initial. Using information about institutional affiliation, we could distinguish persons with the same
name. In a few cases of doubt, information available on their websites was used.
Table 1 Applications by field
and funding instrument
As several researchers applied two or more times during the 3 years, the number of
researchers is smaller than the number of applications: 852 researchers, of which 270 (32
%) female. The advanced career applicants and the open competition applicants belong to
the established generation. The young career grant is clearly for the new generation of
scientists. This means we can distinguish two generations of researchers:
356 young researchers, having finished their Ph.D. studies within the last 3 years;
496 established researchers, generally within the associate or full professor rank.
Full and associate professors are generally older than 40, with an average of 51 years
and a standard deviation of 7 years. Those with an ACG grant are on the younger side
within this group: they are in average 40 years old with a standard deviation of 4 years.
The ECG grantees represent the young researchers; in our sample, they are between 27
and 41 years, with a few older: researchers who got their Ph.D. at an older age. In average,
the young researchers are 33 years old, with a standard deviation of 3 years.
For this paper we define research performance as the number of articles in scholarly
(peer reviewed) journals, and as the number of citations received. Research managers and
science policy makers increasingly emphasize this type of output and the performance
indicators based on it.4 More specifically, we measured scholarly performance of all
researchers, in terms of publications and citations received in the 3 years before the
applicationso we take recent performance and not lifetime performance into account.
The social sciences are heterogeneous, and consist of psychology, education, pedagogy,
anthropology, sociology, communication studies, geography, demography, economics and
law. As publication and citation patterns differ between these fields, performance should be
standardized in order to use the social and behavioral sciences as one population. However,
as Table 1 shows, three fields dominate the applications: psychology, economics and law.
In this paper, we therefore do the analysis first for the (unstandardized) total sample, and
then repeat it for the psychology and economics individually.
4 Of course, this does not cover all scientific output, let alone the societal output of researchers (De Jong
et al. 2011).
Fig. 2 Productivity by gender, established generation social sciences, NL, 20032005
First of all, distribution of research performance is heavily skewed. A small number of the
researchers produce the far majority of publications, and a large amount of researchers
have a very small outputtherefore we use non-parametric statistics.
In the established generation, we have 496 applicants, of which about 22 % are female.
In the 3 years period, male researchers did publish in average more than female researchers
(mn5 = 4.3 publications vs. mn = 3.0). The distribution of publications by gender for the
established generation (ACG and OC) is shown in Fig. 2. Clearly, the distributions are very
skewed, and we test whether these distributions differ significantly. They do: (mdn6 = 2
vs. mdn = 1, MannWhitney U = 18666.5, p = 0.047).
Also in line with earlier findings, in the established generation male researchers receive
more citations than female researchers do (mn = 25.9 vs. mn = 19.5). The differences are
smaller than in the publications. Figure 3 presents the again skewed distributions. The
difference between the distributions is significant, using a MannWhitney test (male:
mdn = 3 vs. female: mdn = 1, U = 18525.5, p = 0.034).
Changing gender differences?
We repeated the analysis for the young generation (ECG applicants) with a different result.
First of all, of the 356 applicants, about 45 % are female. This is a huge increase compared
with the established generation (females 22 %). In the young generation of scientists, the
publication differences have disappeared (Fig. 4). Male and female researchers publish in
average about equal (mn = 1.7 vs. mn = 1.5). Also here we compare the distributions, but
the MannWhitney test shows that they do not differ significantly (male: mdn = 1 versus
female: mdn = 0, U = 14288.5, p = 0.126).
5 mn = mean.
6 mdn = median.
Fig. 3 Impact by gender, established generation social sciences, NL, 20032005
Fig. 4 Productivity by gender, young generation social sciences, NL, 20032005
Also the citation patterns have changed, and differences have disappeared more or less
(Fig. 5). Male researchers have a higher median (mdn = 1 vs. mdn = 0) but a lower
average (mn = 8.4 vs. mn = 10.5) and the MannWhitney test fails to show a significant
difference between the distributions (U = 15105.5, p = 0.522).
Summarizing for the young researchers, in the top of the distribution (the top 7 %)
women outperform men (Table 2). So if there is a gender-based difference, female
researchers outperform males, especially in the top of the ranking. This result differs from
what we found for the established generation and is generally found in the literature: an
overrepresentation of female researchers in the lower part of the distribution, and an
Fig. 5 Impact by gender, young generation social sciences, NL, 20032005
Table 2 Performance by gender
% Female in top
% Female in top
a For older generation: [10 publications, for younger generation: [4
b For older generation: [12 publications, for younger generation: [5
c For older generation: [60 citations, for younger generation: [25
overrepresentation of male researchers in the higher part of the distribution. In Table 2 we
also summarize the impact of the young generation by gender. In the top 10% impact
ranks, female researchers are overrepresented.
A more detailed view on specific disciplines: psychology and economics
The previous analysis was done at the level of the social sciences as a whole. What if we
focus on specific disciplines? We took two social science disciplines with the highest
number of applications and in which English language journal articles are the main form of
Also within the group of the established psychology researchers, males (N = 100) in
average outperform females (N = 41) in publications (Mn = 9.3 vs. Mn = 5.7,
Table 3 Performance by genderpsychology
% Female in top
% Female in top
a For older generation: [17 publications, for younger generation: [6
b For older generation: [20 publications, for younger generation: [7
c For older generation: [150 citations, for younger generation: [40
p = 0.047; Mdn = 6 vs. Mdn = 3, U = 1380.5, p = 0.002) and in citations (Mn = 73.9
vs. Mn = 46.4, p = 0.17; Mdn = 47 vs. Mdn = 13, U = 12590.0, p = 0.000).
The younger generation (N = 87) consists of more women than men, as about 55 % is
female. Here, the picture is differentin line with the findings for the social sciences as a
whole. Output differences have disappeared between male and female researchers
(Mn = 2.31 vs. Mn = 2.48, p = 0.754; Mdn = 2 vs. Mdn = 2, U = 915.0 p = 0.855) in
the younger generation, as have citation differences (Mn = 14.64 vs. Mn = 18.48,
p = 0.543; Mdn = 5 vs. Mdn = 6, U = 880.0, p = 0.625).
The gender differences in the young generation are not significant, although in this case
female researchers show a higher performance. As shown in Table 3, the female
researchers are underrepresented in the higher part of the ranking of the established
generation, but they are overrepresented in the top of the younger generation ranking.
In line with the general findings, in economics established male researchers have more
publications (Mn = 3.6 vs. Mn = 1.4, p = 0.20; Mdn = 2 vs. Mdn = 1, U = 304.0,
p = 0.169), and receive more citations (Mn = 11.5 vs. Mn = 2.1, p = 0.171; Mdn = 3
vs. Mdn = 0, U = 292.0, p = 0.123) than established female researchers do. The
differences are considerable, however not statistically significant due to sample size.
In contrast to the psychology case, within economics young male researchers still have a
higher performance than females do (publications: Mn = 1.4 vs. Mn = 0.8, p = 0.151;
Mdn = 1 vs. Mdn = 0, U = 797.0, p = 0.012/citations: Mn = 4.7 vs. Mn = 4.2,
p = 0.857; Mdn = 1 vs. Mdn = 0, U = 867.0, p = 0.043). But the differences have
become considerably smaller as the averages show. Nevertheless, the female economists
are still stronger represented than male economists in the group of low performing
researchers, although less pronounced as in the older generation.
Table 4 shows that in the established generation women are not present in the in the top
10 % of the population. Yet, they are slowly entering the higher performance groups. This
may suggest a similar generational trend as observed in psychology and within social
sciences as a whole. If this is the case, economics clearly lags behind.
A factor that may explain this observation could be the relatively low share of female
researchers within economics. In the established generation (N = 102), women are some 9
% and in the younger generation (N = 107) this has increased to 27 %. However, within
psychology the comparable figures are 29 and 55 %.
Table 4 Performance by gendereconomics
% Female in top
% Female in top
a For older generation: [8 publications, for younger generation: [2.5
b For older generation: [9 publications, for younger generation: [3
c For older generation: [31 citations, for younger generation: [10
Conclusions and discussion
Our analysis suggests that the gendered performance differences are disappearing. In the
older generation, men outperformed women in terms of publications and citations, but this
is not any more the case in the younger generation. In other words, the traditional
performance differences seem to disappear over time. The data even suggest that female
researchers have started to outperform male researchers. This is in line with experiences in
other parts of the education system, where female pupils and students are increasingly
doing better than male.
This finding is significant as earlier studies found that the performance gap between
male and female researchers emerged in the early career phase (Symonds et al. 2006), and
exactly in this phase the differences seem to be disappearing. This also suggests that the
gendered division of domestic labor, and gender differences in motivation and career
planning, may be weakening. As publication and citation scores are increasingly
influencing academic careers, the disappearing performance differences may be a stimulus for
changing gender relations within science. Of course, the question has to be answered as
whether performance differences now emerge in later phases of the research career, a
question that requires additionalpreferably longitudinalresearch.
The current analysis is restricted to the social sciences, and it would be useful to extend
the analysis to other fields, such as science, technology, engineering and medicine.
Possible performance differences in these fields may be partly due to the low number of
female researchers in many of these fields. However, it is also often argued that men have
better math and science capacities than women, which would lead to performance
differences. This question has been studied intensively, and research suggests these
differencesas far as they existare decreasing over time (Hyde et al. 1990; EACEA 2009).
Furthermore, this study is on a west European case. As the position of women (and
consequently of female researchers) differs between countries, the introduction of a
crosscultural perspective would be another useful extension.
We found differences between the different social and behavioral sciences. For
psychology, we found the same patterns as for the social sciences as a whole. In economics,
gendered performance differences still exists, but are much smaller in the younger
generation as compared with the established generation. The performance gap is narrowing,
but within economics less pronounced than within psychology. This may be related to field
differences in the share of female researchers. Our study indicates that the gender
distribution in the group of active social science researchers has changed considerably. In the
older generation only about 22 % of the applicants are female, in the younger generation
this has increased to 45 %. Within psychology, female researchers even have become the
majority in the younger generation. If mass explains performance, the remaining
performance differences (in fields were the share of women is still relatively low) may
disappear when women would enter those research fields in larger numbers. In those fields,
efforts to increase the number of female researchers remain important.
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