Classifiers trained on data from Waseem and Hovy (2016) and<cite> Waseem (2016)</cite> only predicted a small fraction of the tweets to be racism. Looking at the sexism class on the other hand, we see that both models were consistently classifying tweets in the black-aligned corpus as sexism at a substantially higher rate than those in the white-aligned corpus. Given this result, and the gender biases identified in these data by Park et al. (2018), it not apparent that the purportedly expert annotators were any less biased than amateur annotators<cite> (Waseem, 2016)</cite> .