scholarly journals Gender bias in open source: Pull request acceptance of women versus men

2016 ◽  
Author(s):  
Josh Terrell ◽  
Andrew Kofink ◽  
Justin Middleton ◽  
Clarissa Rainear ◽  
Emerson Murphy-Hill ◽  
...  
Keyword(s):  
Open Source ◽  
Gender Bias ◽  
Open Source Software ◽  
Women In The Workplace ◽  
Pull Request ◽  
Acceptance Rates

Biases against women in the workplace have been documented in a variety of studies. This paper presents the largest study to date on gender bias, where we compare acceptance rates of contributions from men versus women in an open source software community. Surprisingly, our results show that women's contributions tend to be accepted more often than men's. However, when a woman's gender is identifiable, they are rejected more often. Our results suggest that although women on GitHub may be more competent overall, bias against them exists nonetheless.

scholarly journals Gender differences and bias in open source: Pull request acceptance of women versus men

2016 ◽  
Author(s):  
Josh Terrell ◽  
Andrew Kofink ◽  
Justin Middleton ◽  
Clarissa Rainear ◽  
Emerson Murphy-Hill ◽  
...  
Keyword(s):  
Gender Differences ◽  
Open Source ◽  
Gender Bias ◽  
Open Source Software ◽  
Women In The Workplace ◽  
Pull Request ◽  
Acceptance Rates

Biases against women in the workplace have been documented in a variety of studies. This paper presents the largest study to date on gender bias, where we compare acceptance rates of contributions from men versus women in an open source software community. Surprisingly, our results show that women's contributions tend to be accepted more often than men's. However, women's acceptance rates are higher only when they are not identifiable as women. Our results suggest that although women on GitHub may be more competent overall, bias against them exists nonetheless.

scholarly journals Gender differences and bias in open source: pull request acceptance of women versus men

2017 ◽  
Vol 3 ◽  
pp. e111 ◽  
Author(s):  
Josh Terrell ◽  
Andrew Kofink ◽  
Justin Middleton ◽  
Clarissa Rainear ◽  
Emerson Murphy-Hill ◽  
...  
Keyword(s):  
Gender Differences ◽  
Open Source ◽  
Gender Bias ◽  
Open Source Software ◽  
Large Scale ◽  
Women In The Workplace ◽  
Large Scale Study ◽  
Pull Request ◽  
Acceptance Rates

Biases against women in the workplace have been documented in a variety of studies. This paper presents a large scale study on gender bias, where we compare acceptance rates of contributions from men versus women in an open source software community. Surprisingly, our results show that women’s contributions tend to be accepted more often than men’s. However, for contributors who are outsiders to a project and their gender is identifiable, men’s acceptance rates are higher. Our results suggest that although women on GitHub may be more competent overall, bias against them exists nonetheless.

scholarly journals Gender differences and bias in open source: Pull request acceptance of women versus men

2016 ◽  
Author(s):  
Josh Terrell ◽  
Andrew Kofink ◽  
Justin Middleton ◽  
Clarissa Rainear ◽  
Emerson Murphy-Hill ◽  
...  
Keyword(s):  
Gender Differences ◽  
Open Source ◽  
Gender Bias ◽  
Open Source Software ◽  
Women In The Workplace ◽  
Pull Request ◽  
Acceptance Rates

Biases against women in the workplace have been documented in a variety of studies. This paper presents the largest study to date on gender bias, where we compare acceptance rates of contributions from men versus women in an open source software community. Surprisingly, our results show that women's contributions tend to be accepted more often than men's. However, women's acceptance rates are higher only when they are not identifiable as women. Our results suggest that although women on GitHub may be more competent overall, bias against them exists nonetheless.

scholarly journals Project level effects of gender on contribution evaluation on GitHub

2017 ◽  
Author(s):  
Pascal Brokmeier
Keyword(s):  
Software Development ◽  
Open Source Software ◽  
Data Science ◽  
Large Datasets ◽  
Male And Female ◽  
Sexual Discrimination ◽  
Pull Request ◽  
Discrimination Factors ◽  
Acceptance Rates ◽  
Project Level

Distributed open source software development has largely turned to GitHub, a pull-based software development collaboration platform. Recent studies have deployed data science techniques on the large datasets available about millions of projects on GitHub. Some research has focused on pull request (PR) acceptance predictors and evidence was found of sexual discrimination among members. In this paper I analyzed the influence of gender on PR acceptance on a project level, comparing different popular projects regarding their discrimination factors. Several projects were identified that have significant differences between male and female PR acceptance rates.

scholarly journals Project level effects of gender on contribution evaluation on GitHub

2017 ◽  
Author(s):  
Pascal Brokmeier
Keyword(s):  
Software Development ◽  
Open Source Software ◽  
Data Science ◽  
Large Datasets ◽  
Male And Female ◽  
Sexual Discrimination ◽  
Pull Request ◽  
Discrimination Factors ◽  
Acceptance Rates ◽  
Project Level

Distributed open source software development has largely turned to GitHub, a pull-based software development collaboration platform. Recent studies have deployed data science techniques on the large datasets available about millions of projects on GitHub. Some research has focused on pull request (PR) acceptance predictors and evidence was found of sexual discrimination among members. In this paper I analyzed the influence of gender on PR acceptance on a project level, comparing different popular projects regarding their discrimination factors. Several projects were identified that have significant differences between male and female PR acceptance rates.

scholarly journals Barriers Faced by Women in Software Development Projects

Information ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 309
Author(s):  
Edna Dias Canedo ◽  
Heloise Acco Tives ◽  
Madianita Bogo Marioti ◽  
Fabiano Fagundes ◽  
José Antonio Siqueira de Cerqueira
Keyword(s):  
Software Development ◽  
Computer Science ◽  
Open Source ◽  
Gender Equity ◽  
Gender Bias ◽  
Open Source Software ◽  
Development Projects ◽  
Software Projects ◽  
Team Members ◽  
Workplace Conditions

Computer science is a predominantly male field of study. Women face barriers while trying to insert themselves in the study of computer science. Those barriers extend to when women are exposed to the professional area of computer science. Despite decades of social fights for gender equity in Science, Technology, Engineering, and Mathematics (STEM) education and in computer science in general, few women participate in computer science, and some of the reasons include gender bias and lack of support for women when choosing a computer science career. Open source software development has been increasingly used by companies seeking the competitive advantages gained by team diversity. This diversification of the characteristics of team members includes, for example, the age of the participants, the level of experience, education and knowledge in the area, and their gender. In open source software projects women are underrepresented and a series of biases are involved in their participation. This paper conducts a systematic literature review with the objective of finding factors that could assist in increasing women’s interest in contributing to open source communities and software development projects. The main contributions of this paper are: (i) identification of factors that cause women’s lack of interest (engagement), (ii) possible solutions to increase the engagement of this public, (iii) to outline the profile of professional women who are participating in open source software projects and software development projects. The main findings of this research reveal that women are underrepresented in software development projects and in open source software projects. They represent less than 10% of the total developers and the main causes of this underrepresentation may be associated with their workplace conditions, which reflect male gender bias.

scholarly journals New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems

2021 ◽  
Vol 11 (3) ◽  
pp. 920
Author(s):  
Abdulkadir Şeker ◽  
Banu Diri ◽  
Halil Arslan
Keyword(s):  
Software Development ◽  
Open Source ◽  
Open Source Software ◽  
Recommendation System ◽  
Similarity Score ◽  
Open Source Software Development ◽  
Wide Range ◽  
Pull Request ◽  
The Individual ◽  
Collaboration Platforms

Software collaboration platforms where millions of developers from diverse locations can contribute to the common open source projects have recently become popular. On these platforms, various information is obtained from developer activities that can then be used as developer metrics to solve a variety of challenges. In this study, we proposed new developer metrics extracted from the issue, commit, and pull request activities of developers on GitHub. We created developer metrics from the individual activities and combined certain activities according to some common traits. To evaluate these metrics, we created an item-based project recommendation system. In order to validate this system, we calculated the similarity score using two methods and assessed top-n hit scores using two different approaches. The results for all scores with these methods indicated that the most successful metrics were binary_issue_related, issue_commented, binary_pr_related, and issue_opened. To verify our results, we compared our metrics with another metric generated from a very similar study and found that most of our metrics gave better scores that metric. In conclusion, the issue feature is more crucial for GitHub compared with other features. Moreover, commenting activity in projects can be equally as valuable as code contributions. The most of binary metrics that were generated, regardless of the number of activities, also showed remarkable results. In this context, we presented improvable and noteworthy developer metrics that can be used for a wide range of open-source software development challenges, such as user characterization, project recommendation, and code review assignment.

Open Source Software: A Survey from 10,000 Feet

2010 ◽  
Author(s):  
Stephanos Androutsellis-Theotokis
Keyword(s):  
Open Source ◽  
Open Source Software
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