Author(s):  
Josh Terrell ◽  
Andrew Kofink ◽  
Justin Middleton ◽  
Clarissa Rainear ◽  
Emerson Murphy-Hill ◽  
...  

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.


Author(s):  
Josh Terrell ◽  
Andrew Kofink ◽  
Justin Middleton ◽  
Clarissa Rainear ◽  
Emerson Murphy-Hill ◽  
...  

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.


2017 ◽  
Vol 3 ◽  
pp. e111 ◽  
Author(s):  
Josh Terrell ◽  
Andrew Kofink ◽  
Justin Middleton ◽  
Clarissa Rainear ◽  
Emerson Murphy-Hill ◽  
...  

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.


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

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.


2016 ◽  
Author(s):  
Josh Terrell ◽  
Andrew Kofink ◽  
Justin Middleton ◽  
Clarissa Rainear ◽  
Emerson Murphy-Hill ◽  
...  

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.


Author(s):  
Fadi P. Deek ◽  
James A. M. McHugh
Keyword(s):  

2010 ◽  
Author(s):  
Amanda J. Koch ◽  
Susan D'Mello ◽  
Paul R. Sackett

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