2019Unpublished venueRequires access

Investigating the Effects of Gender Bias on GitHub

Nasif Imtiaz, Justin Middleton, Joymallya Chakraborty, Neill Robson, Gina R. Bai, Emerson Murphy-Hill

Open publisher page 96 citations

Abstract

Diversity, including gender diversity, is valued by many software development organizations, yet the field remains dominated by men. One reason for this lack of diversity is gender bias. In this paper, we study the effects of that bias by using an existing framework derived from the gender studies literature.We adapt the four main effects proposed in the framework by posing hypotheses about how they might manifest on GitHub,then evaluate those hypotheses quantitatively. While our results how that effects of gender bias are largely invisible on the GitHub platform itself, there are still signals of women concentrating their work in fewer places and being more restrained in communication than men.

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What this paper is about

Diversity, including gender diversity, is valued by many software development organizations, yet the field remains dominated by men. One reason for this lack of diversity is gender bias. In this paper, we study the effects of that bias by using an existing framework derived from the gender studies literature.We adapt the four main effects proposed in the framework by posing hypotheses about how they might manifest on GitHub,then evaluate those hypotheses quantitatively. While our results how that effects of gender bias are largely invisible on the GitHub platform itself, there are still signals of women concentrating their work in fewer places and being more restrained in communication than men.

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OpenAlex reports 96 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Diversity, including gender diversity, is valued by many software development organizations, yet the field remains dominated by men. One reason for this lack of diversity is gender bias. In this paper, we study the effects of that bias by using an existing framework derived from the gender studies literature.We adapt the four main effects proposed in the framework by posing hypotheses about how they might manifest on GitHub,then evaluate those hypotheses quantitatively. While our results how that effects of gender bias are largely invisible on the GitHub platform itself, there are still signals of women concentrating their work in fewer places and being more restrained in communication than men.

Key concepts: Gender bias, Gender diversity, Diversity (politics), Computer science, Field (mathematics), Software, Data science, Work (physics)

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