Multi-Dimensional Gender Bias Classification
Table 7: Genderedness of offensive content. We measure the percentage of utterances in both the ”safe” and ”offensive” classes that are classified as masculine-gendered, among utterances that are classified as either masculine- or feminine-gendered. We test the hypothesis that safe and offensive classes distributions of masculine-gendered utterances differ using a t-test and report the p-value for each dimension.
['[BOLD] Percentage of masculine-gendered text  [ITALIC] Dim', '[BOLD] Percentage of masculine-gendered text  [ITALIC] Safe', '[BOLD] Percentage of masculine-gendered text  [ITALIC] Offensive', '[BOLD] Percentage of masculine-gendered text  [ITALIC] t-statistic', '[ITALIC] p-value']
We observe that, on the self and partner dimensions, the safe data is more likely to be labeled as feminine and the offensive data is more likely to be labeled as masculine. We test the hypothesis that these distributions are unequal using a T-test, and find that these results are significant.