A Rubric to Identify Misogynistic and Sexist Texts from Software Developer Communications
Background: As contemporary software development organizations are dominated by males, occurrences of misogynistic and sexist remarks are abundant in many communities. Such remarks are barriers to promoting diversity and inclusion in the software engineering (SE) domain.
Aims: This study aims to develop a rubric to identify misogynistic remarks and sexist jokes specifically from software developer communications.
Method: We have followed the systematic literature review protocol to identify 10 primary studies that have characterized misogynistic and sexist texts in various domains.
Results: Based on our syntheses of the primary studies, we have developed a rubric to manually identity various categories of misogynistic or sexist remarks. We have also provided SE domain specific examples of those categories.
Conclusions: Our annotation guideline will pave the path towards building automated misogynistic text classifier for the SE domain.