We conclude that while meta analyses of the bias metrics proposed by <cite>(Bolukbasi et al. 2016)</cite> indicate that the metrics capture and somewhat quantify sociologically meaningful biases present in learned embedding spaces, the metrics are highly sensitive to the hyperparameter configurations of the algorithms used to learn them.