secPrimary Studies

# Women’s Participation in Open Source Software: A Survey of the Literature

Bianca Trinkenreich<EMAIL_ADDRESS>Northern Arizona
UniversityFlagstaff,AZUSA ,  Igor Wiese<EMAIL_ADDRESS>Universidade
Tecnológica Federal do ParanáCampo Mourão,PRBrazil ,  Anita Sarma
<EMAIL_ADDRESS>Oregon State UniversityCorvalis, ORUSA ,  Marco
Gerosa<EMAIL_ADDRESS>Northern Arizona UniversityFlagstaff,AZUSA and
Igor Steinmacher<EMAIL_ADDRESS>Universidade Tecnológica Federal do
ParanáCampo Mourão,PRBrazil and Northern Arizona UniversityFlagstaff,AZUSA

(2020)

###### Abstract.

Participation of women in Open Source Software (OSS) is very unbalanced,
despite various efforts to improve diversity. This is concerning not only
because women do not get the chance of career and skill developments afforded
by OSS, but also because OSS projects suffer from a lack of diversity of
thoughts because of a lack of diversity in their projects. Studies that
characterize women’s participation and investigate how to attract and retain
women are spread across multiple fields, including information systems,
software engineering, and social science. This paper systematically maps,
aggregates, and synthesizes the state-of-the-art on women’s participation in
Open Source Software. It focuses on women’s representation and the
demographics of women who contribute to OSS, how they contribute, the
acceptance rates of their contributions, their motivations and challenges, and
strategies employed by communities to attract and retain women. We identified
51 articles (published between 2005 and 2021) that investigate women’s
participation in OSS. According to the literature, women represent about 9.8%
of OSS contributors; most of them are recent contributors, 20-37 years old,
devote less than 5h/week to OSS, and make both non-code and code
contributions. Only 5% of projects have women as core developers, and women
author less than 5% of pull-requests but have similar or even higher rates of
merge acceptance than men. Besides learning new skills and altruism,
reciprocity and kinship are motivations especially relevant for women, but can
leave if they are not compensated for their contributions. Women’s challenges
are mainly social, including lack of peer parity and non-inclusive
communication from a toxic culture. The literature reports ten strategies,
which were mapped to six of the seven challenges. Based on these results, we
provide guidelines for future research and practice.

††copyright: acmcopyright††journalyear: 2020††journal: POMACS††journalvolume:
37††journalnumber: 4††article: 111††publicationmonth: 8††ccs: Software and its
engineering Software evolution††ccs: Human-centered computing Open source
software††ccs: Social and professional topics Women

##  1\. Introduction

The effects of gender111In this study, we use the term “gender” as a socially
constructed concept (Butler, 1999) where gender identification, display, and
performance might or might not align with the sex assigned at birth. To
reflect this social concept of gender, in this paper, we use the term “women”
and “men” as a shorthand for people who self-identify as such. diversity in
OSS projects has gained increasing attention from practitioners and
researchers (Wurzelová et al., 2019; Robson, 2018; Bosu and Sultana, 2019;
Vasilescu et al., 2015b; Catolino et al., 2019; Fossatti, 2020). Gender
diversity has a positive effect on productivity as it brings different
perspectives together, improving outcomes (Vasilescu et al., 2015b), problem-
solving capacity, and leading to a healthier work environment (Earley and
Mosakowski, 2000). A gender-diverse team has been shown to increase innovation
and productivity in software engineering (Østergaard et al., 2011; Vasilescu
et al., 2015b; Tourani et al., 2017).

However, although open source software (OSS) organizations have been taking
actions to increase gender diversity and place more women in management
positions, the numbers are still low. Women represent only 5.2% of
contributors in Apache Software Foundation (Sharan, 2016) and 9.9% in Linux
kernel (Bitergia, 2016), two of the largest and best-known OSS communities.
Moreover, women represent only 9% of GitHub users (Vasilescu et al., 2015c).

Researchers have been trying to understand the low representation rate of
women in OSS, as well as to learn more about their challenges and the
strategies that can be adopted to attract and retain this underrepresented
population. Existing research suggests that gender bias and sexist behavior
pervades OSS (Nafus, 2012; Gallego et al., 2015). Women reported that feel
frustrated when they are the only woman on a development team and when their
input is not requested, despite their competence in certain areas of the
project (Lee and Carver, 2019). While OSS projects idealize a strict
meritocracy in which quality speaks for itself (Feller and Fitzgerald, 2000),
there are several biases that undermine women, who feel their quality is not
able to speak for itself and report experiencing the “impostor syndrome”
(Vasilescu et al., 2015b). Gender biases can represent a “glass floor” and a
persistent barrier to entry (Mendez et al., 2018; Padala et al., 2020). To
avoid negative bias, some women hide their gender by using neutral aliases
(Lee and Carver, 2019; Vasilescu et al., 2015a).

Although there are many published scientific studies investigating women’s
participation in Open Source Software, the findings are scattered in multiple
fields and venues, and the results are disconnected from one another.
Summarizing and aggregating existing research can help communities fully
comprehend women’s participation in OSS to define proper mechanisms to
increase the number of women contributors and produce new knowledge by
connecting previously dissociated research. Therefore, the purpose of this
study is as follows:

Purpose. To review, summarize, and synthesize the current state of research on
women’s participation in Open Source Software.

Through a systematic mapping of the literature including database search,
backward and forward snowballing, and input from prolific authors, we selected
and retrieved information from 51 primary studies published between 2000 and
2021. Our contributions include identifying: the frequency of women’s
participation, the characteristics of the women who contribute to OSS, the
ways women contribute and the acceptance rates of their contributions, their
motivations to participate, the challenges they face as OSS contributors, and
the strategies OSS communities can employ to help attract and retain women.

##  2\. Research Method

Figure 1. Steps and phases of Systematic Mapping, adapted from (Kitchenham and
Charters, 2007)

We performed a systematic mapping of the literature (SML) approach because we
expected existing research to be fragmented and not follow common terminology
or use established theoretical concepts. The systematic mapping of the
literature is suitable in such circumstances because it maps the available
evidence (Petersen et al., 2008; Petersen et al., 2015), categorizing and
aggregating knowledge dispersed across disconnected studies. This section
details our method, which is based on established guidelines (Petersen et al.,
2015; Kitchenham et al., 2010).

Fig 1 depicts the steps and phases of our research method. We started by
Planning the SML. Three researchers had four meetings to formulate research
goals and questions, elaborate the search protocol, define the inclusion and
exclusion criteria, and test the search protocol. We piloted the search in
Google Scholar and selected four control papers, then executed the search
string again and validated that the control papers could be retrieved. We then
moved to the second stage of Conducting SML, in which we executed the search
string in the selected databases, conducted backward and forward snowballing,
contacted the most prolific authors, applied the inclusion and exclusion
criteria to filter the studies, and extracted data to answer the research
question.

###  2.1. Planning the SML

In the planning phase, we formulated the search protocol, selection criteria,
databases, and search string. We also defined control papers and piloted the
study.

####  2.1.1. Research Goals

To understand women’s participation in OSS projects, we formulated the
following research question: “How has participation by women in OSS
characterized in the literature?”.

When analyzing the selected primary papers, we categorized the participation
of women in OSS from 7 different perspectives:

1\. Representation of women in OSS projects The literature presents different
statistics for women’s representation in OSS, which were measured in different
ways, at different moments, and considering different set of projects. We aim
to aggregate the results, providing a more comprehensive view of the
phenomenon. Linking data obtained from different sources may provide
researchers with an expanded view of the phenomenon under study, prompting new
insights and allowing for further discoveries (Robles et al., 2014).
Additionally, analyzing women’s representation at different time periods can
help us understand the evolution of gender imbalance.

2\. Demographics of women contributors to OSS Understanding the
characteristics (e.g., education level, age, geolocation, tenure) of women who
contribute to OSS projects can help communities and researchers to refine
their strategies to attract profiles of women who are still not participating
and retain women who currently contribute to OSS.

3\. Types of contributions that women make in OSS projects The OSS landscape
has changed since the early 2000s to include the participation of ever more
people and companies. Project-centric roles are becoming more established, and
OSS projects increasingly include community-centric roles, which relate to
areas beyond programming (Trinkenreich et al., 2020). Understanding how women
contribute to OSS projects can help attract both code developers as well as
those interested being part of OSS via non code-centric roles.

4\. Acceptance rate of women’s contributions in OSS projects Anecdotes about
gender bias appear across the literature (Terrell et al., 2017; Kofink, 2015),
and women have been reported to feel that such biases are to blame for their
contributions’ comparatively low acceptance rate (Canedo et al., 2020). We aim
to aggregate the scientific evidence about gender bias and understand what
impact such biases have on the acceptance of women’s contributions.
Understanding the biases can help steer future research and community policies
and can inform current and future contributors.

5\. Motivations that drive women to participate in OSS projects Research has
shown that women are more motivated to use technology to accomplish a goal
rather than for fun (Burnett et al., 2010). For the past 20 years, much
academic work has theorized about and empirically examined OSS contributors’
motivations. Retrieving and consolidating women’s motivations from the
existing studies is relevant to communities seeking to recruit and retain
women. Proper management of motivation and satisfaction helps software
organizations achieve higher productivity levels and avoid turnover, budget
overflows, and delivery delays (Beecham et al., 2008; França et al., 2011; da
Silva and França, 2012).

6\. Challenges faced by women when contributing to OSS projects Previous work
investigated challenges faced by OSS contributors who are mentors and
newcomers (Steinmacher et al., 2015; Balali et al., 2018; Mendez et al., 2018;
Steinmacher et al., 2016). Some of them report gender bias as a challenge
(Balali et al., 2018), and others report barriers faced by women (Dias Canedo
et al., 2019). Understanding the nuances of women’s challenges to contribute
to OSS can help communities plan strategies to mitigate these challenges and
thereby attract and retain more women.

7\. Strategies to increase women’s participation in OSS projects Strategy
proposals are scattered and rarely widely adopted. OSS communities need a
concise view of the different types of actions to select the ones that are
viable and appropriate for their needs and for the challenges they face.

####  2.1.2. Search Protocol and Selection Criteria

We designed a study protocol to conduct a systematic mapping of the
literature, which includes paper collection (database search, snowballing, and
top-authors validation) and filtering. The filtering was applied according to
the following Inclusion (IC) and Exclusion (EC) criteria.

  * •

IC1. The paper explicitly reports women’s degree of participation,
characteristics, performed activities, motivations, challenges or barriers
faced, or strategies used to attract or retain women as OSS contributors.

  * •

EC1. The publication is just an abstract

  * •

EC2. The publication is not written in English

  * •

EC3. The publication is a copy or an older version of another article already
considered

  * •

EC4. The publication is not a peer reviewed paper

  * •

EC5. The publication is a doctoral/master’s dissertation, research plan, short
paper, or report thereof

  * •

EC6. It was not possible to access the complete work.

####  2.1.3. Databases and Search String

We used a hybrid strategy (Mourão et al., 2020) to collect primary studies,
including database search (IEEE Xplore, Scopus, the ACM Digital Library and
Scopus) (Petersen et al., 2015), snowballing, and contact with the most
prolific authors. The selected databases are suggested by Kitchenham and
Charters (Kitchenham and Charters, 2007) to conduct secondary reviews on
computer science and software engineering topics, and in our experience
provide good coverage. Similar to related work (Cosentino et al., 2017; Munir
et al., 2016; Marques et al., 2014; Elberzhager et al., 2012), we limited the
search to title, abstract, and keywords. Table 1 provides the search string
used for each database.

The first part of the search string (before the AND) aims to limit the results
to studies about women or the diversity and heterogeneity they can represent.
The second part of the search string (after the AND) seeks to limit results to
Open Source Software. All searches were completed on November 15, 2020.

As we depicted in Table 1, to avoid missing studies that do not directly
mention the terms “women” or “female” in the title, abstract, or keywords, we
included in the search string more generic terms such as “diversity” and
“gender”, understanding that diversity can include many other aspects (e.g.
culture, age, tenure) and that gender can refer to genders beyond our focus on
women.

####  2.1.4. Control Papers and Piloting

Before searching the selected databases, we conducted exploratory searches
using Google Scholar to refine the inclusion and exclusion criteria, the
research question, synonyms for the search string, and the information
extraction template. From that exploratory search, based on our experience we
selected four well-known, relevant studies to act as control papers (Robles et
al., 2016; Vasilescu et al., 2015a; Terrell et al., 2017; Canedo et al.,
2020). In our pilot studies to test the protocol, all four control papers were
found.

Table 1. Database Search Strings and Results

Database | Search String | Results
---|---|---
Scopus |  | TITLE-ABS-KEY((woman OR women OR female OR gender OR diversity OR ”heterogeneous team”)
---
AND (”open source” OR ”open-source” OR ”free software” OR foss OR floss* OR
oss))
1067
IEEE |  | (”All Metadata”:woman OR ”All Metadata”: women OR ”All Metadata”: diversity OR
---
”All Metadata”: female OR ”All Metadata”: ”heterogeneous team” OR ”All
Metadata”: gender)
AND (”All Metadata”:”open source” OR ”All Metadata”:”open-source”
OR ”All Metadata”:”free software” OR ”All Metadata”: OSS
OR ”All Metadata”: FOSS OR ”All Metadata”: FLOSS*)
350
Compendex |  | (((((woman OR women OR female OR gender OR diversity OR ”heterogeneous team”)
---
AND (”open source” OR ”open-source” OR ”free software” OR foss OR floss* OR
oss))))
100
ACM |  | Title:(((woman OR women OR female OR gender OR diversity OR ”heterogeneous team”)
---
AND (”open source” OR ”open-source” OR ”free software” OR foss OR floss* OR
oss)))
OR Abstract:(((woman OR women OR gender OR diversity)
AND (”open source” OR ”open-source” OR ”free software” OR foss OR floss* OR
oss)))
OR Keyword:(((woman OR women OR gender OR diversity)
AND (”open source” OR ”open-source” OR ”free software” OR foss OR floss* OR
oss)))
879

###  2.2. Conducting the SML

We executed the research protocol, summarized in Fig.1), which comprised the
following six steps to execute the search string in selected databases, remove
duplicates between databases using manual de-duplication, read and filter the
papers applying IC and EC, execute snowballing, and contact the most prolific
authors to find additional studies.

Figure 2. Steps to Filter and Select the Primary Studies

Step1: Executing Search. In November 2020, we performed the search on the
selected search databases and found 2,396 papers. Fig. 1 shows the number of
papers selected in each step of the selection process. We refer to the
selected primary studies with ‘PS’ (e.g., (PS1)) to distinguish them from
citations to other references (e.g., [1]).

Step2: Remove Duplicates. We used a spreadsheet to store and organize the
retrieved papers, and we ordered the papers by title and manually removed 482
duplicates, avoiding automatic removal.

Step3-4: Select Primary Studies. Selection of papers followed the guidelines
proposed by Kitchenham and Charters (Kitchenham and Charters, 2007) and
Petersen et al. (Petersen et al., 2015) using the steps shown in Fig.1. In the
first step, we analyzed only the paper’s title and abstract, consulting the
entire text only when necessary to reach a confident judgment. In the second
step, we filtered the papers considering the full-text reading. In both
filters, papers were included to match the inclusion criteria or excluded if
they fit any exclusion criteria.

Step5: Backward and Forward Snowballing: For Backward Snowballing, we
conducted a single-step snowballing sampling, checking the papers’ references
and looking for additional relevant papers. This step resulted in four
additional primary studies. For Forward Snowballing, we also conducted a
single-step sampling, checking what other papers cited the selected papers.
This step resulted in nine additional primary studies.

Step6: Contact prolific authors. We reviewed the publication records and
contacted the top 3 most prolific authors, who are arguably specialists in the
field. We searched for the Google Scholar profile and personal website of
these authors and sent emails to them showing the list of primary papers and
asking if they suggest others that we missed and should be included. This step
resulted in three additional primary studies.

Table 2. The categories of data to explain women’s participation in OSS and the respective primary studies that provide data to answer them Categories of Data - Women’s Participation |  Primary Studies
---|---
1\. Representation of women in OSS projects |  (PS2; PS3; PS4; PS5; PS9; PS12; PS16; PS17; PS21; PS43; PS44; PS46; PS49; PS51)
2\. Demographics of women contributors to OSS |  (PS1; PS2; PS3; PS4; PS5; PS6; PS7; PS8; PS16; PS28; PS45; PS46)
3\. Types of contributions that women make in OSS projects |  (PS2; PS4; PS5; PS6; PS9; PS10; PS11; PS12; PS13; PS14; PS15; PS45; PS46)
4\. Rate of acceptance of women’s contributions in OSS projects |  (PS4; PS6; PS10; PS14)
5\. The motivations that drive women to participate in OSS projects |  (PS5; PS16; PS18; PS19; PS50; PS51)
6\. The challenges faced by women when contributing to OSS projects |  (PS13; PS18; PS20; PS21; PS22; PS23; PS24; PS25; PS26; PS27; PS28)
| 7\. The strategies been proposed for OSS communities to increase
---
women’s participation in OSS projects
(PS3; PS6; PS8; PS9; PS12; PS16; PS23; PS24; PS25; PS26; PS27; PS28; PS29;
PS30; PS31; PS32; PS33; PS34; PS35; PS36; PS37; PS38; PS39; PS40; PS41; PS42;
PS47; PS48)

###  2.3. Extracting and Analyzing Data

We extracted quantitative data from the papers to analyze what the literature
had presented about women’s representation in OSS projects and the rate of
acceptance of women’s contributions. In order to analyze women’s
representation in OSS projects, we pulled the percentage of women and how the
study measured women’s participation. We then grouped the findings according
to the data source (e.g., mined from software repositories and mailing lists,
surveys). In order to analyze the rate of acceptance of women’s contributions
in OSS projects, we extracted findings about the reported acceptance rate of
contributions made by women to OSS projects.

We qualitatively analyzed the papers and inductively applied open coding to
understand what is being reported by literature about the demographics of
women who contribute to OSS, the types of contributions they make, their
motivations, challenges and strategies. For types of contributions and
motivations, the coding approach was informed by previous work. To answer
types of contributions, we followed the classification defined by Trinkenreich
et al. (Trinkenreich et al., 2020), which categorizes coders and non-coders,
and project-centric and community-centric roles. For motivations, we used the
theoretical framework of OSS motivations proposed by Von Krogh et al.(Von
Krogh et al., 2012), which is a comprehensive investigation that aggregates
motivation factors found in 40 primary studies published since 2009. The
authors grouped the OSS motivation factors in ten main categories, namely,
_Ideology_ , _Altruism_ , _Kinship_ , _Fun_ , _Reputation_ , _Reciprocity_ ,
_Learning_ , _Own-Use_ , _Career_ , and _Pay_.

For challenges and strategies, we built post-formed codes and as the analysis
progressed associated them with respective parts of the studies’ text. Three
of the authors conducted three card sorting sessions (Spencer, 2009) and
discussed the codes and categorization until reaching consensus about the
meaning of and relationships among the codes.

##  3\. Characterizing the Studies

In the following we present some data about the primary studies (e.g., where
they were found, when they were published, and who published them).

###  3.1. Where were studies published?

Fig. 3 shows the distribution of the 35 papers selected from the search
engines. The Compendex digital database search did not return any new
publications, only duplicated ones.

Figure 3. Distribution of the selected papers among the search engines

###  3.2. When were the studies published?

Fig. 4 shows the number of primary studies published per year. The earliest
paper was published in 2000. There were up to six papers per year until 2019,
after which we saw a noticeable peak. We included one paper from 2021 through
forward snowballing, but decided to not include it in Fig. 4.

Figure 4. Publications per year

###  3.3. Who has published the studies?

We ranked all 118 authors by the number of publications in the sample to
investigate the most prolific authors. Among them, 95 authors had one paper;
17 authors had two papers; five authors had three papers; two authors had four
papers; and one had 6 papers. Two researchers authored more primary studies
namely Alexander Serebrenik (10), and Bodgan Vasilecu (7).

##  4\. Results

In this section, we present the results based on the seven perspectives

###  4.1. Representation of women in OSS projects

The primary studies identified women participation using a variety of methods,
including mining software repositories and mailing lists and analyzing
demographics from OSS surveys and mentorship programs. Table 3 summarizes the
frequency reported by the primary studies.

Distribution of women in OSS found via mining software repositories. From a
dataset of 23,493 GitHub projects, Vasilescu et al. (PS17) used the
genderComputer tool (PS49) (with 93% of precision) to identify the gender,
based on personal names, and, if available, countries, of 873,392 GitHub
contributors. They found 91% men and 9% women. From a dataset of 8,338 GitHub
projects, Prana et al. (PS16) found that the percentage of new GitHub accounts
created by women has remained around 10% between 2014-2018. Bosu and Sultana
(PS9) analyzed a dataset of 683,865 code review requests from 10 popular OSS
projects. They found that women represent 6.70% (out of 4,543) of non-casual
developers (those who submitted at least five code changes) and only 4.27%
(out of 936) of core developers (those who are the top 10% developers in terms
of the number of code commits in a project). Imtiaz et al. (PS3) used the same
GitHub dataset and similar technique to infer gender and could identify
564,929 GitHub profiles into 529,253 men (93.7%) and 35,676 women (6.3%). From
the 5,250 OpenStack contributors, Izquierdo et al. (PS12) inferred the gender
and found that 10% are women. From a random sample of 300,000 GitHub users
from a dataset with 16M users, Qiu et al. (PS46) identified 9.7% as women.
Terrel et al. (PS4) analyzed a GitHub dataset with 4,037,953 profiles and
identified the gender of 1,426,127 (35.3%) through their public Google+
profiles. From those profiles, the authors analyzed pull-request submission
and acceptance by women and men and found that 8,216 of the pull-requests were
submitted by women (5.2%) and 150,248 (94.8%) by men. Kofink (PS10) also
analyzed a dataset of 1,811,631 pull-requests and found that 4.5% were
submitted by women and 95.5% by men. Zacchiroli (PS44) also analyzed the
authors of contributions. With 1.6 billion commits from the combined projects
of GitHub, GitLab, and other development forges (using
222https://www.softwareheritage.org/), corresponding to the development
history of 120 million projects, the author found that contributions were
authored by 33 million distinct people over 50 years, and that in 2019 10% of
all contributions to public code were authored by women.

Distribution of women in OSS found by mining mailing lists: Kuechler et al.
(PS23) analyzed the participation in eleven mailing lists of six projects
(Buildroot, Busybox, Jaws, Parrot, uClibc, and Yum), which totaled 3,310
subscriptions. Authors found low participation by women: 8.27% of all
subscribers, 6.63% of those who posted one message, 2.5% of those who posted
more than ten times, and 1.5% of code reporters. Vasilescu et al. (PS49) also
used the mailing lists of two projects (Drupal and Wordpress) to explore
women’s representation and found that women authored 9.81% of the messages in
Drupal and 7.81% in Wordpress. In contrast, both men and women engage in OSS
projects for statistically similar lengths of time.

Distribution of women in OSS through surveys: Mani and Mukherjee (PS2) and
Robles et al. (PS5) analyzed the same FOSS 2013 survey data (Arjona-Reina et
al., 2014). This survey was answered by 2,183 OSS contributors, 226 of whom
identified as women (10.35%). Lee and Carver (PS21) received 119 answers to
their questionnaire where 10.92% of respondents identified as women, while
Gerosa et al.’s (PS51) questionnaire received 224 answers with 7.6% who
identified as women.

Distribution of women who participate in mentorship programs: By analyzing the
gender of Google Summer of Code participants from 2016 to 2018, Canedo et al.
(PS43) found that while there is a minor variation across the years, the
volume of women stayed close to 11.98% of the total number of participants in
the program. 333The Google Summer of Code (GSoC) is a 3-month OSS engagement
program that offers stipends and mentorship to students willing to contribute
to OSS projects (Silva et al., 2017; Trainer et al., 2014; Silva et al.,
2020b).

In summary, the primary studies reported women’s participation ratios ranging
between 4% to 14% (median 9.8%, as can be seen in Fig. 5a) across different
measurements and OSS communities. When we analyze the distribution over time
based on when the primary studies were published (Fig 5b), barring some
fluctuation, women’s participation ratio is more or less stable at around 10%.
However, when taking a broader timeline view, Zacchiroli (PS44) through his
analysis of public code contributions over the last 50 years found that
women’s contributions appear to be on the rise and are rising faster than
those by male authors. This shows that while much still needs to be done, OSS
projects are getting more gender diverse, albeit slowly.

Table 3. Frequency of women’s participation in OSS as reported by primary studies (ordered by year) Measure | Women
---|---
OSS contributors - survey (2013) (PS2; PS5) | 10.4%
Participation in Wordpress mailing lists (2014) (PS49) | 7.8%
Participation in Drupal mailing lists (2014) (PS49) | 9.8%
Authors of Pull-Requests (2015) (PS10) | 4.5%
GitHub users (2015) (PS17) | 9.0%
GSoC mentors 2016 (PS43) | 7.8%
GSoC students 2016 (PS43) | 11.9%
GSoC mentors (2017) (PS43) | 11.9%
GSoC students (2017) (PS43) | 13.4%
GitHub committers (2018) (PS16) | 5.9%
GitHub account owners (2018) (PS16) | 10.0%
OpenStack contributors (2018) (PS12) | 10.0%
GSoC mentors (2018) (PS43) | 10.9%
GSoC students (2018) (PS43) | 14.2%
Core Developers (2019) (PS9) | 4.3%
Authors of Pull-Requests (2019) (PS3) | 6.3%
Non-Casual Coders (2019) (PS9) | 6.7%
GitHub users (2019) (PS46) | 9.7%
Authors of contributions to public code (2019) (PS44) | 10.0%
OSS contributors - survey (2019) (PS21) | 10.9%
OSS contributors - survey (2021) (PS51) | 7.6%
Figure 5. The frequency of women’s participation in OSS as reported by primary studies (a) per measurement and (b) per year. The values comprise percentages of women measured by different mechanisms. Table 4. Descriptive statistics of women’s participation reported by primary studies | % Women
---|---
Mean | 9.114
Median | 9.750
Mode | 10.000
Std. Deviation | 2.654
Minimum | 4.300
Maximum | 14.200
25th percentile | 7.525
50th percentile | 9.750
75th percentile | 10.775

Women represent about 9.8% of OSS contributors, considering different types of
participation over the years.

###  4.2. Demographics of women contributors to OSS

To get a deeper understanding of the demographics of women who contribute to
OSS projects, we analyzed available data reported in the primary studies along
the following criteria: education level, time dedicated to contributions,
diversification of projects, age range, family status, tenure, and geolocation
(Fig 6).

Figure 6. The characteristics of women who contribute to OSS projects

Education Level. Based on Stack Overflow’s 2018 developer survey that included
43,000+ OSS contributors, Wurzelova et al.’s (PS7) study reported that 82.8%
of women who contribute to OSS are at least undergraduate students, against
76% of the overall rate of contributors (Overflow, 2018). Mani and Mukherjee
(PS2) found a similar rate (81.4%) using data from the 2013 FLOSS Survey (226
women), while the corresponding figure for the whole dataset is 72%. All the
36 developers who identified as women on the survey from Canedo et al. (PS6)
were at least undergraduate students. A substantial number of contributors
from the three studies were post-graduates, who either achieved a Master’s
degree—11.6% (PS6), 27.6% (PS7)— or Ph.D.—4.2% (PS7), 10% (PS2), 22.9% (PS6).

Volunteering. Half of the 226 women (53.59%) who answered the 2013 FLOSS
questionnaire devote less than five hours per week to OSS projects. Only
14.77% of the women who answered this questionnaire dedicate more than 40
hours per week (PS5), which can represent OSS as a full-time job. Although not
mentioning the number of hours per week, according to the Powell et al.’s
(PS28) results, 89% of women said they contribute to OSS both at home and at
work, which includes bringing their work home and contributing to OSS during
their leisure time.

Diversification of projects. By mining data from software repositories, three
studies (PS3; PS4; PS46) concluded that women concentrate their efforts on
fewer projects than men. From a dataset of 152,534 pull-requests created by
20,926 women and 3,135,384 pull-requests created by 308,062 men, Imtiaz et al.
(PS3) concluded that women’s pull-requests are concentrated in fewer projects
and fewer organizations than men’s. Indeed, Qiu et al. (PS46) analyzed a
balanced sample of the dataset, including 28,995 women and 29,096 men and also
concluded that women tend to concentrate their contributions in fewer
different projects than men. From a dataset of 1,426,127 users whose gender
could be identified, Terrell et al. (PS4) analyzed the acceptance of submitted
pull-requests and concluded that women contribute to fewer projects than men.
From another perspective, Vasilescu et al. (PS1) ran a survey answered by 199
women and 611 men, in line with the previous studies, and concluded that women
own fewer public repositories than men.

Age. In different ways, four studies (PS1; PS5; PS6; PS8) show that most women
who contribute to OSS are older than 20 and younger than 37 years old.
According to the 226 women who answered the FLOSS 2013 questionnaire, the
median age women join OSS is 26, the mean is 28, 1st Qu. is 22 and 3rd Qu. is
33, when many are already professionally active (PS5). Having a similar
result, the median age of the 199 women who answered the Vasilescu et al.
(PS1)’s questionnaire was 29, the mean is 31, 1st Qu. is 24 and 3rd Qu. is 37.
More than half (52%) of the 58 women who answered Singh’s (PS8) questionnaire
reported being 25-34 years old. Most of the 36 women who answered the Canedo
et al.’s (PS6) questionnaire (80%) were younger than 35 years old.

Family Status. Almost half of the 226 women who took part in the FLOSS 2013
survey are not married or do not live with their partners (PS2). This rate was
composed of 35% OSS single women, over 11% women not living with their
partners, 3% living with their partners, 3% married, 0.1% separated from their
partners (PS2) and 20% of those OSS women have children (PS2; PS5).

Geolocation. The majority of women who participated in the primary studies
were from Brazil (44% (PS1)), USA (37.1% (PS1)—40% (PS2)), and Germany (6%
(PS2)—9% (PS16)—14.3% (PS1)). Considering the overall contributors from all
genders, the USA is top ranked (25% (PS2)–32.6 (PS1)), followed by Germany
(6.5% (PS1)–8% (PS2)). Brazil had only 2.7% of the overall contributors (PS1),
but 44% of the overall women, showing that women stand out amongst
contributors from this country.

Tenure. Most (77.2%) of the 199 women who answered Vasilescu et al.’s (PS1)
questionnaire contribute to open source projects for fewer than five years.
Authors found that women have on average six years of experience in
IT/programming, a significantly lower tenure than men with nine years of
experience;

The majority of women contribute to OSS projects for $<5$ years, devote $<5$
hours per week to OSS, are from multiple continents, are at least
undergraduate students, with age ranging between 20-37 years, concentrate
their work in a small number of repositories, projects, and organizations, and
are mostly unmarried and with no children.

###  4.3. Types of contributions that women make in OSS projects

While the primary type of contribution in OSS projects is related to code
development, the roles available in OSS projects go beyond the project-centric
roles (Trinkenreich et al., 2020). They include many people who work “behind
the scenes” to drive and sustain the community (PS11). We categorized the
activities reported by primary studies according to a framework of OSS roles
from a previous study (Trinkenreich et al., 2020) with two perspectives:
coders or non-coders, and project-centric or community-centric (Fig.7).
Afterward, we present details about women’s contributions as coders and non-
coders reported by primary studies.

Figure 7. Women make OSS contributions both as coders and as non-coders Figure
8. Community-Centric and Project-Centric roles reported by primary studies as
played by women who contribute to OSS. Roles can be played in parallel.
Adapted from (Trinkenreich et al., 2020)

####  4.3.1. Coders

Only 31% of the 226 women who answered the FLOSS survey (PS5) contribute to
OSS projects are code developers, and 24% perform coding in parallel with
other roles.

Core Developers. The classic hierarchical model of coders in OSS development
communities is described as a core-periphery structure, with a small number of
core developers and a large set of peripheral developers (Nakakoji et al.,
2002). The core developers are code contributors involved with the OSS project
for a relatively long time who make significant contributions to guide the
project’s development and evolution. Due to their relevant contributions and
interactions, core developers often play leadership roles in OSS projects (Ye
and Kishida, 2003). Related to these developers, Canedo et al. (PS6) found
women as core developers in only 5.24% of the 711 GitHub analyzed projects. Of
all the core developers, only 2.3% were women. From a dataset of 683,865 code
review requests from ten popular OSS projects, Bosu and Sultana (PS9) found
that women comprise a maximum of 10% of core developers among all ten
projects. Following a classification of commit types from Hattori and Lanza
(Hattori and Lanza, 2008), Canedo et al. (PS6) concluded that women who are
core developers contribute more with corrective and reengineering commits than
forward engineering and management commits. Moreover, when describing the
commits, women present a more detailed message explaining their contribution
changes than men. (PS15) evaluated the interactions in projects Angular.js,
Moby, Rails, Tensorflow, Django, Elasticsearch and found that women who are
core developers are more likely than men to interact with other contributors,
evolve similarly to men within the project, and, though underrepresented,
contribute to building sustainable social capital for OSS.

Preferred Technologies. From the 711 projects analyzed by Canedo et al. (PS6),
women represented 8.8% of the core developers in projects that are based on
Scala programming language, 8.7% when is CSS, 6.3% when in TypeScript, 5.6%
when is Swift, only 1% when the project is based on PHP and Shell programming
languages. Still, from the same data, even projects written in TypeScript
(10.93%) have at least one woman as a core developer, and 2.17% of projects
using PHP have at least one woman as a core developer. Considering the data
from the six projects analyzed by El Asri and Kerzazi (PS15) (Angular.js,
Moby, Rails, Tensorflow, Django, Elasticsearch), women represented at least
4.8% of core developers for the projects based on Python, at least 4.5% for
C++, and at least 4.2% for Java. From the 158,464 of pull-requests for which
Terrell et al. (PS4) could identify gender, women had a greater rate of
accepted pull-requests in Ruby, Python, and C++. We present the percentages of
women as developers for each programming language as reported in the primary
studies in Fig 9.

Figure 9. Women’s participation as core Developers in OSS per programming
language

Code reviewers. Peer code review is a practice in software engineering. A code
developer submits the code produced to another person (peer) to evaluate and
find possible errors before merging the code to the project codebase
(Bacchelli and Bird, 2013). According to the GitHub dataset of six projects
evaluated by Paul et al. (PS13), women are more likely to write reviews
expressing sentiments in the text to another woman than to a man during code
reviews. Huang et al. (PS14) used medical imaging and eye-tracking to evaluate
the visual and cognitive processes and patterns of neural activation followed
by reviewers while performing code reviews. Authors found that women spent
significantly more time analyzing pull-request messages and author pictures
(regardless of their identity) than the code itself when performing code
reviews.

####  4.3.2. Non-Coders

Almost half (45%) of the 226 women who answered the FLOSS 2013 survey take
part in non-coding activities, and 24% perform code-related activities in
parallel with other roles (PS5).

OSS Community Manager. After analyzing the career pathways followed by 17
contributors, Trinkenreich et al. (PS11) presented a set of community-centric
roles, including community founders and managers, strategists, mentors,
writers, license managers, treasures, and advocates. The contributors who play
these roles are usually “hidden figures,” who are not visible when analyzing
the data from projects’ repositories or coding platform websites. 11 (out of
the 12) women interviewed in this study play community-centric roles.

Project Leader/Manager. More than half (51.49%) of the 226 women who answered
the FLOSS 2013 survey participate in community leader, coordinator, or
administrator roles, while only 5% of those women coordinate more than three
projects (PS5). Women in OpenStack who play leadership roles represent 7% of
the project committee members, 8% of the project team leaders, 9% of the
project board directors, 7% of the technical committee, 8% of the working
group leaders, and 23% of project ambassadors (PS12).

Women are more present in community-centric roles; 45% of them make non-code
contributions. However, they often play both coding and non-coding activities
in parallel. Only 5% of projects have at least one woman as a core developer.
When reviewing code, women also read pull-request messages and analyze the
author’s pictures.

###  4.4. Rate of acceptance of women’s contributions in OSS projects

For code contributions, we used the merge rate of pull-requests as a
measurement of women’s contributions’ acceptance. Kofink (PS10) analyzed
1,811,631 pull-requests from 1,049,345 different users and found that women’s
pull-requests account for only 4.5% of the total. Terrell et al. (PS4)
presented a similar rate: women submitted 5% of the pull-requests (from
158,464 in which authors could identify gender) and tend to have their pull-
requests accepted at a slightly higher rate (78.7%) than men (74.6%),
regardless of experience level. Authors found that, while less experienced
developers making their initial pull requests do get rejected more often,
women generally still maintain a higher rate of acceptance throughout. Even
submitting fewer pull-requests, according to Kofink (PS10), women have 64.2%
of merge acceptance rate, nearly equivalent to men’s (63.9%), and continue to
have high acceptance rates as they gain experience. According to Huang et al.
(PS14), humans (non-bots) are 4.7% more likely to accept pull-requests
submitted by women than men. On the other hand, Terrell et al. (PS4) found
that women have a 12% lower pull-request acceptance rate when they explicitly
identify themselves as women, comparable to 3.8% for men who disclosure their
gender. Even in a population of core developers, one-third of the 36 women who
answered Canedo et al.’s (PS6) survey reported they believe that reviewers had
not accepted at least one of their contributions due to gender bias. Moreover,
11.4% women often recognize gender bias while someone assesses their
contributions.

Women author less than 5% of pull-requests. However, they have similar or even
higher rates of merge acceptance than men. On the other hand, women frequently
report biases and they have lower acceptance rates of their pull-requests when
they explicitly identify themselves as women.

###  4.5. The motivations that drive women to participate in OSS projects

We consolidated the studies reporting women’s motivation to participate in OSS
projects, aggregating the results according to Von Krogh et al. ’s categories
(Von Krogh et al., 2012). Von Krogh et al. (Von Krogh et al., 2012) surveyed
the literature and identified ten categories of motivation, grouped as
intrinsic, internalized-extrinsic, and extrinsic. Intrinsic motivation
(Enjoyment and Fun, Kinship, Ideology, and Altruism) moves a person to act for
the fun or challenge entailed rather than in response to external pressures or
rewards (Ryan and Deci, 2000). In contrast, extrinsic motivations (Career and
Pay) are based on outside incentives when people change their actions due to
an external intervention (Frey, 1997). Contributors can also internalize
extrinsic motivators (Learning, Own-Use, Reciprocity, and Reputation) as self-
regulating behavior, rather than as external impositions (Deci and Ryan, 1987;
Roberts et al., 2006). We summarize our findings organized in these higher
level categories in Table 5 and Figure 10.

Table 5. Women’s motivations to participate on OSS projects |  Categories (Von Krogh et al., 2012)
---
Women’s motivations to participate on OSS
Intrinsic | Enjoyment and Fun |  Contribute when “find it exciting” (PS18), have fun and feel stimulated by writing programs(PS51).
Kinship |  Work on a project with friends (PS16) and participate in new forms of cooperation (PS5)(PS51)
Ideology |  Believe that source code should be open and want to limit the power of proprietary software companies (PS5) (PS51)
Altruism |  Share knowledge (PS5)(PS51), improve other developers’ code (PS5), help people and practice philanthropy (PS19)
Extrinsic | Career |  Improve career (PS51) and have more job opportunities (PS5).
Pay |  Being paid to contribute or selling products and services related to OSS (PS16)(PS51).
Internalized Extrinsic | Learning |  Learn, develop and improve skills (PS5)(PS51)
Own-Use |  Employment needs to use (PS50) (PS51)
Reciprocity |  | Feel personal obligation because they use OSS (PS51)
---
Reputation |  | Want to enhance my reputation (PS51)
---
Figure 10. Women’s motivations to contribute to OSS. Based on (Von Krogh et
al., 2012)

Among all 10 categories, the literature showed that women see Enjoyment and
Fun, Reciprocity, Kinship, and Pay a little differently from the motivation
literature (Hertel et al., 2003; Hars and Ou, 2004; Lakhani and Wolf, 2003;
Ghosh et al., 2002; PS51) —which is based on surveys answered predominantly by
men—reports. Enjoyment and Fun has been consistently reported as a top driver
to contribute to OSS in motivation surveys (Lakhani and Wolf, 2003; Hars and
Ou, 2004; Ghosh et al., 2002; Hertel et al., 2003; PS51). However, according
to the stratified analysis on Gerosa et al.’s (PS51) study, no women reported
this motivation to join (and one–6%–stayed because of this), while 7% of the
men joined motivated by fun and 20% continued because of it.

The opposite trend is observed for Reciprocity, Kinship, and Pay. Reciprocity
appeared as one of the top motivators for women in Gerosa et al.’s (PS51)
work, who reported that 39% of the women reported this as motivation to
continue (versus 15% of the men). In general surveys (Lakhani and Wolf, 2003;
PS51), reciprocity is not among the top motivators. Regarding Kinship, while
39% of the 226 women who answered the FLOSS survey joined because of this
motivation, 31% continued because of it (PS5). Most (64%) of the 22 women who
answered Prana et al.’s survey (PS16) select a project in which friends and
colleagues also participate. As part of kinship, peer parity also plays a role
in women’s motivation (PS50). David and Shapiro (PS50) found that social
connections with other developers influence women’s choices. However, no women
from Gerosa et al.’s (PS51) study joined OSS because of kinship. Kinship is
not top ranked in general surveys (Hars and Ou, 2004; Lakhani and Wolf, 2003;
Ghosh et al., 2002), but this trend has been changing with the rise of social
coding platforms (PS51). Regarding Pay, Prana et al. (PS16) indicated that
payment is a greater incentive for women than men (64% vs. 35%). This was
echoed by women interviewees from Balali et al. (PS18). However, the
difference was not noticed in Gerosa et al.’s (PS51) work, in which men and
women equally reported money as a reason to continue contributing (14% and
11%, respectively).

For other motivations, we found that women follow a similar trend as reported
in the general literature. Learning, for example, has been frequently reported
as a key motivation to contribute to OSS (Lakhani and Wolf, 2003; Hertel et
al., 2003; Hars and Ou, 2004; Ghosh et al., 2002) and most (68%) of the 226
women who took part in the FLOSS 2013 survey joined for Learning and 65%
continue because of it (PS5). The same happens for Altruism. It is a common
OSS motivator in OSS (PS51; Ghosh et al., 2002) and it is relevant for women
as well—37% of the women who took the FLOSS 2013 survey reported that they
joined to share knowledge (PS5) and 22% from another work continued because of
it (PS51).

Similar rates were also found for Career, Own-Use, and Reputation. Regarding
Career, only 4% of the 226 women who took the FLOSS 2013 survey and none who
took Gerosa et al.’s (PS51) survey reported joining to improve their careers.
Similar rates were found for men (5% and 8%, respectively). For Own-Use, David
and Shapiro (PS50) found that women are motivated by their employment-related
needs and one third (6 out of 18) of the women from Gerosa et al.’s (PS51)
reported this motivation to join OSS. This is in line with previous research
that shows that women are more motivated to use technology for what it enables
them to accomplish (Burnett et al., 2010). Reputation was not a top motivation
for contributors from all genders in the early 2000s (Lakhani and Wolf, 2003;
Ghosh et al., 2002) and is still not. Only 4% of the men from from Gerosa et
al.’s (PS51) joined because of reputation, while no women reported it.

Finally, an interesting case was Ideology, which was top-ranked in general
surveys about motivation to join OSS (Lakhani and Wolf, 2003; Hertel et al.,
2003; Hars and Ou, 2004; Ghosh et al., 2002) from the 2000s. Ideology is
usually captured by motivations as “software should be free for all,” “free to
modify and redistribute,” or “OSS should replace proprietary software.” (Von
Krogh et al., 2012). In the recent survey by Gerosa et al. (PS51), this
motivation has dropped some and was mentioned as a reason to join by only 11%
of the women and 11% of the men. When considering only women, we can see that
there was also a drop compared to the FLOSS survey, in which ideology was
mentioned by 28% of the women (PS5).

Reciprocity, Kinship and Pay are motivations specially relevant for women. On
the other hand, enjoyment and fun motivate men more than women. Altruism,
learning, and own-use motivate both men and women, career and reputation are
low-ranked for both genders, and ideology was relevant in the past but lost
importance for both genders over the years.

###  4.6. The challenges faced by women when contributing to OSS projects

Women mainly face social challenges when contributing to OSS (PS21), which can
also influence their decision to leave an OSS project (PS13). In Powell et
al.’s (PS28) survey, 37 women answered; 50% of them indicated they had
witnessed gender-based discrimination within the OSS community either online,
in meetings, or in class, and 50% said they had experienced harassment online
or offline. Gender-related incidents can be so severe that they motivate women
to leave an OSS project (PS1). Indeed, in another survey (PS21) women reported
that they drop out when the OSS project does not care about diversity. Leaving
an OSS project is a decision that impacts more women than men—according to Qiu
et al. (PS46), and women are more likely to disengage from GitHub by 27%.
Understanding the reasons behind the decisions to step out of a project can
help create strategies to increase retention in OSS. Kuechler et al. (PS23)
suggest that women drop out because the OSS project is not aligned to their
motivations or due to the unappealing and hostile social dynamics in projects.
We summarize the challenges, which were all social, in Table 6 and Fig. 11 and
mark with an asterisk (*) the ones reported as a challenge that ultimately can
cause women to leave OSS. Next, we present and explain each of them.

Table 6. Challenges faced by women when contributing to OSS projects Challenge | Description
---|---
Lack of Peer Parity |  Women feel alienated (PS28), frustrated (PS1), invisible (PS24) and less comfortable without other women around (PS18), specially in medium-size projects where all contributors (PS27).
| Non-Inclusive
---
Communication
The expletives often used in the mailing lists (PS13), documentation (PS18)
and code reviews (PS27) are insulting to women and can cause them to leave an
OSS project (PS13).
Toxic Culture |  Incidents of symbolic violence, harassment (PS24) and sexism against women (PS22) bring hostility (PS25) and can hinder their access to the community (PS21), as they may already be hesitant about how they will be received (PS23).
Impostor Syndrome |  Even being competent (PS32) and knowing the importance of confidence (PS28), women face a lack of self-efficacy (PS18) (PS21; PS29; PS30; PS31), are more restrained (PS3) and reluctant to publicly display their work (PS1) than men in general
| Community
---
Reception Issues
Finding a mentor is a hard task (PS21), as men consider as a dating
opportunity (PS22), which leads many women to hide their gender (PS1) and feel
restrained when being repealed by communities for not being ready to provide
contributions soon (PS20).
Stereotyping |  Women are being boxed into specific roles (PS24) (PS26), sometimes treated by men as if they were their mother for who they ask how to dress and behave (PS22)
| Work-Life
---
Balance Issues
Lack of time due to family responsibilities (PS21)
Figure 11. Challenges faced by women when contributing to OSS

Lack of Peer Parity. Most women (72%) feel outnumbered and 24% feel alienated
(PS28). Women reported to feel more comfortable and accepted by their same
gender counterparts (PS18) and feel frustrated when there is no peer parity
(PS1). This problem worsens in medium-size projects in which all contributors
are men, as they may form a clique that a woman contributor could have
difficultly breaking into (PS27). “It is not so common to find many girls in
technical teams” (PS6), and in the face of this lack of parity women reported
to feel invisible in larger majority-men groups (PS24).

Non-inclusive communication. Expletives often used in the mailing lists are
insulting to women. The negative workplace experience of encountering words
that are demeaning to them in the mailing lists can cause women to leave OSS
projects (PS13). Awkward communication styles (PS18) on acrimonious talk about
which code piece should be incorporated (PS22), and terms usually associated
with men (e.g., “guys”) can demotivate women (PS27).

Toxic Culture. Incidents of symbolic violence and harassment against women can
hinder their access to the community, as when men decide to ’Hire that one
because she is hot’ (PS24). Geek-saturated communities like Slashdot are often
unwelcoming and hostile environments (PS25). Additionally, women are
sexualized in OSS (PS8), facing judgment, abuse, hostility, and discrimination
(PS42). While hurtful and offensive talk is openly addressed to them, women
are obliged to remind men not to “stare and point” at them (PS22). From the 13
women who answered a questionnaire sent to 15 OSS projects, 38% had suffered
some incidents of sexism, including sexist statements or assumptions, being
ignored, insinuations that they had it easy because they were women, and being
simultaneously held to higher standards than men and underestimated (PS21).
Moreover, the authors found that women had trouble being taken seriously and
needed to prove themselves (prove-it-again (PS3)). According to to (PS23),
public flaming and aggression can be enough to distort women’s participation,
as they may already be hesitant about how they will be received.

Impostor Syndrome. Women tend to be risk-averse (Dohmen et al., 2011) and have
low computer self-efficacy (Burnett et al., 2010, 2011; Cazan et al., 2016;
Hartzel, 2003; Huffman et al., 2013; Singh et al., 2013), which can affect
their behavior with technology, causing women to be less confident in their
ability to complete tasks and blame themselves if there is a problem (PS29;
PS30; PS31). Women find it challenging to directly translate competence to
confidence without social attraction (being liked by the other community
members in terms of having a rapid increase of followers). Consequently,
initiating a pull-request to a new repository can be problematic due to
women’s competence-confidence gap (PS32). Even understanding that confidence
is an essential factor when entering OSS (PS28), women face a lack of self-
efficacy (PS21; PS18). “Despite having proved [their] competency in certain
areas of the code/project, [their] opinion is rarely or never asked for”
(quotation from Vasilescu et al. (PS1)). Still, Imtiaz et al. (PS3) found that
women tend to be more restrained than men in general. Despite being
knowledgeable and professionally well-settled, women may be more reluctant to
publicly display their work (PS1).

Community Reception Issues. Women reported to feel restrained when communities
nullify them when they do not have enough skills to provide contributions
since the first day (PS20). When trying to find a mentor, upon discovering
their mentee’s gender, men mentors can treat the relationship as a dating
opportunity (PS22). This makes finding a mentor an arduous task, which
includes attracting attention and breaking into a close-knit OSS community
(PS21). Many women use a fake GitHub and hide their gender, “so that people
would assume [they] were male” (PS1).

Stereotyping. Pre-existing stereotypes (PS8; PS28), gender roles, and “macho”
attitudes can cause gender inequalities in OSS communities (PS24). Women are
boxed into specializations despite their manifest protest against it, as the
legal case against the front-end/back-end distinction has shown (PS26).
Additionally, men often treat women as if they were their mother, asking for
advice about how to dress and behave and then refusing to enter into a
technical dialogue thereafter (PS22).

Work-life Balance Issues. Women that participated in Lee and Carver’s (PS21)
study reported a lack of time and family responsibilities. Only women from
this study reported family responsibilities as a challenge.

Women face social challenges that include: missing having other women around
(lack of peer parity), insulting expletives in mailing lists (non-inclusive
communication), suffering symbolic violence and harassment (toxic culture),
avoiding initiating a pull-request due to lack of confidence (impostor
syndrome), facing challenges asking men to serve as their mentor (community
reception issues), being boxed into specific roles (stereotyping), and sharing
time between work and family (work-life balance issues).

###  4.7. The strategies been proposed for OSS communities to increase women’s
participation in OSS projects

Strategies include actionable mechanisms that OSS communities can take and
combine to create a more inclusive environment for women in OSS. We summarize
the propose strategies in Fig. 12 and Table 7. Next, we present and explain
each of them. All strategies had been mentioned as a way to mitigate at least
one challenge presented in Sect. 4.6. However, there was no strategy reported
to mitigate the challenge Work-Life Balance Issues.

Table 7. Strategies to increase women’s participation in OSS projects Strategy | Description
---|---
| Promote awareness of
---
the presence of peers
Reduce the lack of peer parity by having more women involved (PS24) (PS28) and
propagating their participation (PS12) (PS39).
| Promote women-specific
---
groups and events
Awake technological vocations with schoolgirls’ OSS events (PS24) and code
development training (PS35), create forums and women-only spaces (PS6) (PS8)
(PS24) (PS42) (PS28), and facilitate women’s registrations and participation
in events (PS47).
| Promote inclusive
---
language
Avoid gender pronouns (PS6) that assume that people are [all] the same gender
(PS27).
| De-stereotype the
---
OSS contributor
Fix and do not stereotype activities on gender (PS8) (PS28), as code
development for men (PS6) (PS26) and community management for women (PS24).
| Encourage and be
---
welcoming to women
Have women encouraging other women (PS16) (PS25) to make code (PS28) and also
non-code contributions (PS32), increasing their confidence (PS6), while making
the community friendly and supportive (PS8) (PS39) (PS41).
| Promote women to
---
leadership roles (empowerment)
Train women in leadership skills (PS9) (PS38), promote them to senior,
decision-making positions, (PS6) (PS8) (PS16) (PS24) and mediating (PS36)
roles.
De-bias tools |  Use the Gendermag technique to find bias in tools, and use recommendations to adjust the software, making it more inclusive to the women’s cognitive style (PS29) (PS30) (PS31).
| Recognize women’s
---
achievement (visibility)
Showcase the success of women (PS16) (PS42), celebrate their achievements
(PS3), recognize their efforts (PS32) and give credits when they deserve it
(PS8), using either the communication channels (PS6) and events in which they
can be speakers (PS24).
| Prepare Mentors to
---
Guide Women
Train mentors to guide women (PS8) (PS39) (PS40) (PS42), bring cultural
proximity between mentors and mentees (PS16), making sure novices find the
help and support they need (PS23) (PS24).
| Create and enforce
---
a Code of Conduct
Develop a code of conduct (PS3) (PS16) (PS27) (PS47) as the collective norms
on (un)acceptable behavior at all interactions, explicit the prohibition of
harassment (PS21) (PS24) (PS37), and that violations have consequences (PS8)
(PS33), while having mechanisms to invigilate the use and to apply the
punishments accordingly if necessary.

Promote awareness of the presence of peers. Half (54%) of the women
respondents of Powell et al.’s (PS28) study said they would be more inclined
to participate in OSS if there were more women involved. Promoting awareness
about the rate of women can help to attract more women, minimizing the feeling
of alienation (PS28). The awareness should include a measurement of women’s
participation and the type of contributions (PS12; PS39). According to
participants of Calvo’s (PS24) study, the communities can generate parallel
spaces in which the proportion of women is above 50% so as to create more
diverse environments under the values of mediation and care.

Promote women-specific groups and events. The community managers interviewed
by Calvo (PS24) mentioned that they promote schoolgirls’ events to inspire
vocations and empower girls who may opt for an OSS career. This strategy
should promote activities exclusively for women in those spaces, highlighting
their presence, as women tend to be invisible in larger groups in which men
are the majority (PS24). For those women already interested in OSS, promoting
women-only groups, spaces, and events (PS6; PS8; PS24; PS42; PS28; PS47)
fosters discussions, support networking, and empowerment (PS42). Moreover, it
provides a safe space for expressing feelings and opinions (PS24) and
revealing their identities (PS47). Although effective, Singh and Brandon
(PS47) found that only 3% of the 350 projects they analyzed have women-
specific spaces—including websites, IRC Channels, dedicated blogs,
collection/list of resources, dedicated Facebook pages, and local meet-ups.

Promote inclusive language. Avoid gender pronouns that assume that people are
[all] one gender or one demographic (PS27). For example, using ‘guys’ is very
common, and it gives an idea that contributors are men (PS6).

De-stereotype the OSS contributor. The women interviewed in Singh’s (PS8)
study recommended to ”leave the stereotypes out the door.” The frustration
caused by stereotypes was expressed by one of the women surveyed by Canedo et
al. (PS6): ”Stop treating women developers as ’women developers’ and start
treating them as developers.” Powell et al. (PS28) suggests showing less
discrimination and more inclusion to tone down the male-dominated atmosphere
and promote participation. Calvo (PS24) and Vedres and Vasarhelyi (PS26)
suggest avoiding the feminization of specific assignments, like those relating
to community building tasks; OSS communities should re-classify types of work
that used to be packaged in masculine-feminine stereotyped specialties.

Encourage and welcome women. Singh’s (PS8) findings show that being less
judgmental and appreciating diverse teams is essential to supporting and
encouraging women. Indeed, as Beach (PS41) discusses, people need to feel
supported, accepted, and encouraged. This encouragement may even come from
other women (PS16). Powell et al. (PS28) suggested starting by encouraging
small steps as an incentive to women to submit bug reports and share their
input, which was echoed by two participants of Canedo et al.’s (PS6) study,
“the solution is to build confidence” and “not to fear when contributing.”
This would increase their self-confidence (PS25).Encouragement is also the
goal of some initiatives presented by Parker’s (PS25)
FLOSSpols444www.flosspols.org, which offers recommendations on how to solve
the gender gap; these initiatives include WOWEM, a gender equity and OSS
research and education project; and LinuxChix, a community for supporting
women in Linux. There is no value in encouraging women to be there if the
environment is hostile. To welcome women, one of the community managers who
participated in Barcomb et al.’s (PS39) study recommends making the community
friendlier in general.

Promote women to leadership roles (empowerment). A way to empower women is to
have them in senior roles (PS6), in project governance (PS38), and where
appropriate (PS8), as mentioned by one woman participant of Prana et al.’s
(PS16) study: “More women reviewers. More women are acting directly on the
governance of large OSS projects”. Some community managers indicated their
communities created decision-making positions and ensured that women led
public activities (PS24). Catolino et al. (PS36) suggested that a way to avoid
the proliferation of community smells is to involve women in positions where
they can mediate discussions and improve the communication of sub-communities.
According to Singh (PS8), promoting women to positions of authority shows the
project respects their contributions.

De-bias tools. Most (73%) of the barriers that affect software professionals
have some form of gender bias (PS29). Indeed, bias in tools and infrastructure
can hinder women newcomers from joining OSS (PS29). One way to de-bias
infrastructure and tools is by applying the GenderMag technique. GenderMag
uses personas and a specialized Cognitive Walkthrough (CW) to systematically
evaluate software and make them more inclusive of the women’s cognitive style
(PS29; PS30; PS31). This technique’s precision was proved by a lab study that
showed that the GenderMag technique helped to identify 81% of the issues
(Burnett et al., 2016).

Recognize women’s achievement (visibility). When recognizing women’s
achievements, the community provides the social attraction that women seek to
overcome their competence-confidence gap (PS32). Communities can show
recognition by increasing the visibility of women (PS16), listing them as
great contributors whenever they deserve it (PS42), and publicly celebrating
their achievements in blogs, project homepages, and social media (PS3; PS16).
Another way to increase visibility is to organize events where speakers are
women (PS24; PS47). These simple actions inspire more women to participate
(PS16; PS24).

Prepare Mentors to Guide Women. As mentioned before, OSS projects are usually
men-dominated environments, which may scare women away (PS22; Turkle, 2005).
Mentorship can help women newcomers find the assistance and support they need
(PS23; PS24; PS39). One way to do so is to have women mentor other women (PS8;
PS42). Singh (PS8) highlights that when mentoring women it is necessary to
guide them on different aspects. While men need to change their behavior and
projects need to implement systemic changes, Singh (PS8) posits that women
also need to be trained to ignore disruptions and not be easily bothered by
criticism or insults; the mentor needs to be extra supportive, friendly,
respectful, and encouraging (PS8).

Create and enforce a Code of Conduct. Developing a code of conduct for the
community (PS3; PS8; PS16; PS24; PS27; PS33; PS37; PS47) helps to mitigate
Tightrope effects555The term Tightrope is usually associated with the circus,
where a performer walks on a stretched rope. Following an analogy, the term
can refer to the narrow band of socially acceptable behavior for someone, in
our case, women (PS3). by assisting communities in articulating acceptable
behaviors for all members (PS8). The code of conduct comprises the collective
norms of a community, as mantras to shape the culture of collaboration (PS37),
the community’s expectations and values to create a friendly and inclusive
community (PS8; PS33). While having a code of conduct will not prevent sexism,
it indicates to any men who have firmly held anti-female behaviors that such
actions will not be tolerated in the project (PS21). However, according to
Robson’s study (PS34), just creating a code of conduct will not increase
women’s participation. The author showed that projects that introduced a code
of conduct in their history saw women’s participation increase almost at the
same rate of projects without a code of conduct. Projects increased from 2.37%
to 3.81% after a code’s introduction. Projects without codes of conduct,
comparing gender diversity within similar periods yields, had an increase from
4.10% to 5.53%. The average increases were 1.44%, and 1.43%, respectively,
which means creating the code of conduct did not help increase women’s
participation. Robson (PS34) posits that the code of conduct needs to be
enforced among the project members. Indeed, it is necessary to have mechanisms
in place to implement the code and show that violations have consequences
(PS8; PS33).

Figure 12. Strategies employed by OSS communities and projects to increase
women’s participation in OSS Figure 13. The strategies that were mentioned by
primary studies to mitigate challenges faced by women in OSS (circles
represent challenges and rectangles represent strategies)

The strategies that OSS communities can employ to increase women’s
participation include providing awareness and numbers about women
contributors, inclusive language, women-specific groups and events, de-
stereotyping the OSS contributor, encouraging and welcoming women, having
women in leadership, de-biasing tools, recognizing women’s achievement,
preparing mentors to guide women, and creating and enforcing a code of
conduct.

##  5\. Discussion

In this section, we discuss our results.

Spread the word and recognize women’s success. Impostor syndrome is a
psychological concept about a pattern of behavior wherein people (even those
with adequate external evidence of success) doubt their abilities and
experience a persistent fear of being exposed as a fraud (Mullangi and Jagsi,
2019). As we presented in Section 4.3, the literature shows that when women
join OSS, the rate of acceptance of their contributions is similar to (if not
higher than) men’s. The Impostor Syndrome in OSS can arouse from the hostile
and Toxic Culture that pervades communities, which are two of the challenges
we found in the literature and were presented in Section 4.6. The impostor
syndrome disproportionately affects women and other minority groups, who often
lack sufficient role models of success (Mullangi and Jagsi, 2019). In that
sense, the strategies of Promoting awareness about having other women and
Recognizing women’s achievement (visibility) that we presented in Section 4.7
can help to reduce the impostor syndrome that women reported to feel. The
benefits of combining these two strategies are two-fold. While recognition
support the retention of existent women, it also attracts new women who can
see they can have similar success achieved by their peers. Those strategies
have been applied in STEM and other domains. Publicizing success stories of
women in STEM was a strategy used to attract more women in Latin America in
STEM higher education programs (Garcia-Holgado et al., 2019). Establishing
prizes and awards is a strategy that approximately 82% of U.K. research
institutions have applied to stimulate and attract more women in STEM
(Fatourou et al., 2019). In automotive industries, specific groups publish
articles about women and recognize leading women personalities through e-news
(Sultana et al., 2013). As in other domains, OSS projects should implement
different mechanisms to reward and promote awareness of women, motivating them
to stick around.

Believe in OSS as a career. As we could find in Section 4.4, only 4.07% of the
226 surveyed women from the FLOSS 2013 study joined to increase their job
opportunities. After becoming contributors, this motivation increased almost
six times (going to 25.79%) (PS5). We argue that this represents the “shifting
belief” that women have in OSS toward building a career, which increases only
after overcoming the barriers to join and become contributors. The multiple
roles presented in Section 4.3 are both related to the technical (project-
centric) and non-technical (community-centric) side of the projects. Awareness
of the different roles and career pathways that exist in OSS can attract women
with diverse backgrounds and expertise to OSS by showing them the multitude of
trajectories to success (PS11).

The misalignment between women’s motivations and challenges. If women have
social motivations (e.g. Kinship) as we presented in Section 4.5, and the
reported challenges are also social, as we presented in Section 4.6, there is
a conflict between expectations and reality, which can explain why women are
not joining or staying in OSS projects. When women join an OSS project
expecting to find other women (PS50) and friendly colleagues (PS16), but
instead find Lack of Peer Parity and face a Toxic Culture, this directly
conflicts with their motivations.

Women-specific spaces. When offering women-only spaces, OSS communities show
they are welcoming women (PS6). According to one interviewee from Calvo’s
(PS24) study, “when you send things directly to women, they become a lot more
involved”. Women tend to hide their identities and gender to avoid bias and
protect themselves (PS1), but not in women-specific spaces, demonstrating they
felt safe and comfortable in those spaces (PS48). Participants from Canedo et
al.’s (PS6) study mentioned some specific initiatives (e.g., Outreachy666
Outreachy (https://www.outreachy.org/) is a paid, remote internship program
that aims to support people from groups underrepresented in technology, such
as women, helping newcomers to OSS to make their first contributions. Interns
work with experienced mentors from OSS communities in a diverse set of
activities, including code development, user experience, documentation,
illustration, graphical design, or data science. More than 90% of past interns
are women.  and local meetups) that might help to attract more women. Summer
of Code events offer a diverse set of motivations and enhance the
participants’ sense of competence, autonomy, and relatedness, increasing the
chances of future contributions as they internalize OSS projects’ culture and
values (Silva et al., 2020a). Although it is pretty clear that women-specific
spaces and events are essential to create safe spaces and make women
comfortable, these spaces are still not commonplace—found in only 3% of the
350 projects analyzed by Singh and Brandon (PS47). Therefore, community
building teams and maintainers must foster these kinds of efforts to make
women start reporting to feel welcome and supported.

Codes of conduct: reward who follows, punish who violates. Robson (PS34)
concluded that it would make litter difference to have a code of conduct
unless it is enforced among the project members. The authors showed no
significant difference in the proportion of women contributing to projects
with or without a code of conduct. Enforcing compliance with codes of conduct
can be supported by tools like bots (PS8; Wessel et al., 2018). Even though
highly suggested by the literature as a strategy to increase inclusion, Singh
and Brandon (PS47) found that only 8% of the 355 sites of OSS projects that
authors investigated have a code of conduct. To promote OSS projects to adopt
a code of conduct, Prana et al. (PS16) suggested creating a reward program to
recognize the projects that have one (e.g., GitHub could offer donation
through sponsors, badges, etc.).

No stereotypes, please! According to a survey of 5,500 GitHub users (Zlotnick,
2017), women more often than men encounter language or content that makes them
feel stereotyped. Stereotypes manifest the common expectations about members
of certain social groups. Both descriptive (how women are) and prescriptive
(how women should be) gender stereotypes and the expectations they produce can
compromise a woman’s career progress (Heilman, 2001, 2012). Even before
starting a career, stereotype threats represent one of the significant
barriers to underrepresented groups engaging in Computer Science education.
Implicit stereotypes about gender and STEM have profound effects on girls’ and
women’s interest, confidence, and persistence in STEM education and careers
(Dasgupta and Stout, 2014; Dasgupta, 2011). Being afraid of stereotypes can
motivate women to hide their gender (PS1) and create pseudonyms to avoid
judgment (PS21). This behavior was also observed by Ford et al. (Ford et al.,
2019) in online communities, where participants use a “gender neutral alias
for websites like technical communities, because [they] get better help when
asking questions or answering them.” One of the strategies presented in
Section 4.7 is De-stereotyping the OSS contributor, which differs from using a
neutral username to hide gender. In fact, Canedo et al.’s (PS6) study showed
that users who do not reveal their gender suffer an even more severe
disadvantage in survival probability. Although it prevents discrimination by
categorical gender, avoiding gender identity can also lead to a lack of trust
and exclusion from projects and ultimately cause a higher exit rate of such
users. Stereotypes can be minimal but still makes a difference. People’s
attitudes, beliefs, and behavior are often shaped by factors that lie outside
their awareness (Banaji and Dasgupta, 1998; Greenwald and Banaji, 1995).
Considering that even minimal social cues may activate negative stereotypes
early in informational processing (Wu et al., 2020), De-stereotyping the OSS
contributor is crucial for women to start seeing themselves playing the role
of developer and not just men. This strategy is aligned to the suggestion of
women interviewed in the Blincoe et al.’s study (Blincoe et al., 2019), who
considered that changing the typical image of software engineers as men IT
geeks is a way to reduce the gender gap.

Women are as efficient as men… maybe even more. Based on the two code
contribution metrics (i.e., code churn per month and code changes per month),
Bosu and Sultana’s (PS9) evidenced the absence of significant differences when
comparing men and women developers in terms of productivity. Moreover, the
authors suggest that women are as productive as their male colleagues in an
inclusive OSS project, with some women developers demonstrating more
productivity than the average men developers. Even not supporting any
inferences about whether men or women are more accurate at code review,
results from Huang et al. (PS14)’s study indicates women present more reliable
activity patterns.

Free two birds with one key. OSS communities can implement single but
structured actions combining ideas from more than one strategy to increase
women’s participation. By publishing success stories of women on media, OSS
communities can promote awareness of presence of peers to attract more women
and also recognize women’s achievement (visibility) to retain women who are
already contributors. Considering that this media exposure can include women’s
posts and pictures, the action also attends the strategy of de-stereotype the
OSS contributor, which is usually associated with the image of men. Another
action that can attend more than one strategy is to create a women-only forum,
which is part of the strategy to promote women-specific groups and events.
When moderating and analyzing the messages to implement feasible changes to
problems that are being actively discussed, this action also acts to encourage
and be welcoming to women, offering mentorship or inviting women to contribute
to specific activities directly. One more action that can be be adopted in
multiple strategies is to create and enforce a code of conduct and associated
online training, being transparent about the punishments for those who act
against it. There can be one training for contributors in general and another
one for mentors to (prepare mentors to guide women), showing practical
examples of acceptable and non-acceptable behaviors. Communities can use
mining tools to identifying gender pronouns in messages of mailing lists,
pull-requests, and code reviews and help to promote inclusive language. The
authors of those messages can be individually contacted and even receive the
non-compliance punishment.

###  5.1. Gaps in the literature and open opportunities.

This subsection builds upon the discussion and summarizes the gaps in the
literature that may be explored by researchers, in addition to the
opportunities for women, practice, and education.

Researchers: Although several strategies to increase women’s participation
have been proposed in the literature (PS6; PS8; PS16; PS24; PS27), most papers
do not present scientific evidence about the effectiveness of these
strategies. For instance, Tourani et al. (PS33), Imtiaz et al. (PS3), and
Vandana and Brandon (PS47) called for further research to evaluate the
effectiveness and best practices related to code of conduct, despite being one
of the most cited strategy to promote women participation. Izquierdo et al.
(PS12) discuss the difficulty of evaluating the effectiveness of strategies,
as communities need to have consistent measurements before (baseline), during,
and after their implementation. The authors reported that, although OpenStack
created the Women of OpenStack Working Group (which included educational
sessions, professional networking, mentorship, social inclusion, and enhanced
resource access), the OpenStack Foundation did not have baseline information
about the involvement of women.

The literature also reports a diverse set of challenges being faced by women
(PS13; PS18; PS20; PS21; PS22; PS23; PS24; PS25; PS26; PS27; PS28), many of
them without associated strategies or further understanding. There is also no
studies presenting theories to explain why how women leave or (not) join OSS
projects. There are some studies about motivations to participate in OSS
projects (Lakhani and Wolf, 2003; Ghosh et al., 2002; Hars and Ou, 2004;
Hertel et al., 2003), but only a few of them report women’s motivations and
none go deep in this analysis. Moreover, the literature lacks research
exploring why women leave OSS, their motivation to not participate in OSS, and
why a large portion of women who study STEM do not join OSS projects.

Lastly, researchers can use this study’s structure to investigate how the
literature is positioned regarding the participation of other minority
populations in OSS or even different domains.

Education: When knowing the challenges women face, educators can approach them
in the classroom with students from all genders to improve awareness and
discuss possible mitigation actions. This research can also inform educators
who adopt OSS contributions to teach software engineering (Pinto et al.,
2017).

Future Women contributors: When undecided about their future career in IT,
women can find the types of contribution made by other women in the present
study. Although not restricted to the activities presented here, women can be
inspired by other women’s success and motivations to participate, gain
awareness of the challenges reported by other women so they can prepare to
face similar ones, and prioritize participation on projects that follow one or
more reported strategies.

OSS communities: OSS communities that seek to foster gender diversity can
combine and implement the strategies to increase women’s participation, as we
presented in the Discussion section. Moreover, when knowing the
characteristics of women who contribute, the communities can target their
efforts on them, for example, promoting events at universities (as most of the
contributors are at least undergraduate students) and marketing actions
focused on a public whose age range between 20-37.

##  6\. Related Studies

Challenges faced by women in STEM. The gender gas52 is also present in the
science, technology, engineering, and mathematics (STEM) fields at all
education levels and in the labor market (Fatourou et al., 2019). The barriers
faced by women in STEM fields, presented by McCullough (McCullough, 2011), are
similar to some of the challenges we presented in Section 4.6, including
discrimination and implicit bias (Toxic Culture), lifestyle choices, and
family obligations (Work-Life Balance Issues), and lack of role models and
mentors (Community Reception Issues).

Strategies to increase women’s participation in STEM. The W-STEM project
(Garcia-Holgado et al., 2019) seeks to create mechanisms to attract and guide
women in Latin America in STEM higher education programs, including actions to
keep measuring the gender equality in enrollment and retention (as we
presented in the strategy Promote awareness of the presence of peers). Another
strategy proposed by both Garcia-Holgado et al. (Garcia-Holgado et al., 2019)
and Moreno et al.’s (Moreno et al., 2014) study is to disseminate scientific
and technological culture from an early age, promoting STEM studies vocation
and choice in girls and young women in secondary schools (as we presented in
the strategy Promote women-specific groups and events). Moreover, the women
who participated on Moreno et al.’s (Moreno et al., 2014)’s study corroborated
the strategy of promote inclusive language and the need to avoid chauvinistic
attitudes, and to de-stereotype the CS student, suggesting that the general
image of the student majoring in CS should change and not ascribe to the nerd
stereotype anymore. Some women may not want to be perceived as nerds, because
the nerd stereotype is typically ascribed only to men.

There are also previous studies about women’s participation in other cultures
and domains. Analogous to OSS projects, women’s barriers in the medical
profession and their ability to rise to leadership positions are also
influenced by social and cultural context (Ramakrishnan et al., 2014). In the
opposite direction, women are active in war rebel groups where men are often
presumed to be the default gender, and even are frequently involved in
leadership roles (Henshaw, 2016). By analyzing the career trajectories of
women executives across a variety of sectors, Glass and Cook (Glass and Cook,
2016) concluded that while attaining promotion to leadership is not easy,
serving in a high position can be even more challenging. Although women can be
more likely than men to be empowered to high-risk leadership positions, they
often lack the support or authority to accomplish their strategic goals. As a
result, women leaders often experience shorter tenures compared to men peers
(Glass and Cook, 2016). Similar to software development teams, where women are
instrumental to reducing community smells (PS36), in international relations,
the collaboration between women delegates and women civil society groups
positively impacts and brings more durable peace when negotiating peace
agreements (Krause et al., 2018). The challenge of Work-Life Balance that we
presented in Section 4.5 is a general challenge faced by women who aim to work
in Japan, where the low numbers of women in medicine reflect the prevalent
societal belief that careers and motherhood do not mix (Ramakrishnan et al.,
2014). In contrast, Scandinavia has similar numbers of men and women
physicians, which has coincided with the emergence of progressive work–life
policies, the belief that women can combine motherhood and employment, and
changing expectations of work-life balance. Historically, Sweden was the first
country to establish paid parental leave for fathers in 1974, and its National
Labor Market Board has developed statements since 1977 encouraging men to
contribute to childcare responsibilities (Haas and Hwang, 2009).

To the best of our knowledge, there are no other studies aggregating evidence
about women’s participation in OSS projects. Considering that women are still
underrepresented in OSS and projects seek more diversity to increase
productivity and enhance the quality of delivered software, it is crucial to
understand the profile of women who contribute to OSS, their motivations,
challenges, and strategies to attract and retain them.

##  7\. Threats to Validity

We used the checklist provided by Ampatzogloua et al.(Ampatzoglou et al.,
2019) to identify and categorize threats to validity and corresponding
mitigation actions.

Study inclusion/exclusion bias There may be relevant papers in the population
that are not in our sampling frame, e.g., studies that covered women’s
participation in OSS published in outlets that are not indexed by the target
search engines or excluded by the filters we used (see Section 2.1.2). Also,
there may be relevant articles in the sampling frame that are not in the
sample; for example, there may be papers covering women’s participation in OSS
never use the terms we included in the search string. We took several steps to
mitigate these threats, including additional terms besides women in search
string (e.g., diversity and heterogeneous team), backward and forward
snowballing, having the list of primary studies reviewed by the most prolific
authors.

Researcher bias and Repeatability We used an open research question (and
search string) to find all kinds of women’s participation in OSS. This
openness can bring subjectivity to the data extraction and repeatability.
While the first author of this study leaded the execution of steps to filter
and select the primary studies (see Fig 2, other two researchers with
extensive experience in conducting qualitative analysis and literature studies
participated on defining the protocol with phases and steps (see Fig 1),
inclusion and exclusion criteria, and discussed the data in weekly meetings
during the recording process. Besides, one senior researcher cross-checked a
portion of the extracted data. During the weekly meetings, we discussed and
adjusted codes and categories until we reached agreement. In the meetings, we
also checked the consistency of our interpretations.

Robustness of classification We used existent classification schema from
literature to explain two categories of participation: the types of
contributions that women make in OSS projects (see Section 4.3) and the
motivations that drive women to participate in OSS projects (see Section 4.5).
The selection of those two initial classification schema poses a threat, since
they might not be enough to explain the phenomena its tailoring not efficient.
At the same time that we had these schemas to guide our analysis, we
constantly assessed the possibility and need of extending them. Therefore,
although we did not find any new category of motivation to extend Von Krogh et
al.’s (Von Krogh et al., 2012) framework of OSS motivations, we extended the
classification used for types of contributions with new roles that arouse from
the primary studies.

##  8\. Conclusion

In this paper we investigated the women’s participation in OSS projects, in
terms of their participation’s frequency, the demographics of women who
contribute to OSS projects, the types of contributions women make, how well-
succeeded they are being when contributing, their motivations to participate,
the challenges they face and would influence them to leave OSS projects, and
the strategies OSS communities can employ to help mitigating those challenges.

Our findings show that, according to the literature, women represent about
9.8% of Open Source Software contributors, considering different types of
participation. The majority of women contribute to OSS projects for less than
five years, devote less than one work-day to OSS on few repositories, and are
at least undergraduate students. While being more present in community-centric
roles, women are low represented as authors of pull-requests and as core
developers, mostly making non-code contributions. When submitting a pull-
request, women have high rates of merge acceptance, and lower when they
explicitly identify themselves as women. Reciprocity, kinship and getting paid
motivates more women than men. Altruism, learning, and own-use motivate both
men and women, career and reputation are low-ranked for both genders. When
contributing, women face social challenges such as a lack of peer parity, non-
inclusive communication, a toxic culture, impostor syndrome, community
reception issues, stereotyping, and work-life balance issues. OSS communities
that seek to increase women’s participation can mitigate those challenges by
providing awareness about the presence of other women, promoting inclusive
language, organizing women-specific groups and events, de-stereotyping the OSS
contributor, encouraging and welcoming women, placing women in leadership,
adopting de-biasing tools, recognizing women’s achievement, preparing mentors
to guide women, and creating and enforcing a code of conduct.

As future steps, we plan an in-depth analysis of women’s motivations,
challenges, reasons that would make them leave, sense of belonging to the
community, and their perceptions of OSS communities’ success. As a long-term
plan, we will propose strategies to attract and retain more women to OSS
communities.

##  9\. Acknowledgements

This work is partially supported by the National Science Foundation under
Grant Numbers 1815486, 1815503, 1900903, and 1901031.

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* appendixStyle primaryStudies