Investigating the Effects of Gender Bias on GitHub
Autor: | Joymallya Chakraborty, Gina R. Bai, Justin Middleton, Nasif Imtiaz, Neill Robson, Emerson Murphy-Hill |
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Rok vydání: | 2019 |
Předmět: |
Gender diversity
business.industry media_common.quotation_subject Software development 020207 software engineering 02 engineering and technology Open source 020204 information systems 0202 electrical engineering electronic engineering information engineering Gender bias business Psychology Cognitive psychology Diversity (politics) media_common |
Zdroj: | ICSE |
DOI: | 10.1109/icse.2019.00079 |
Popis: | 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 show 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. |
Databáze: | OpenAIRE |
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