We compare our results to previous results from debiased and non-debiased word embeddings<cite> (Bolukbasi et al., 2016)</cite> . Bolukbasi et al. (2016) propose to identify gender bias in word representations by computing the direction between representations of male and female word pairs from the Definitional List ( − → he-−→ she, −−→ man-− −−−− → woman) and computing their principal components.