diff --git a/fairlearn/reductions/_moments/cdf_demographic_parity_moment.py b/fairlearn/reductions/_moments/cdf_demographic_parity_moment.py
index 4cdcfdff3..8fb1fec55 100644
--- a/fairlearn/reductions/_moments/cdf_demographic_parity_moment.py
+++ b/fairlearn/reductions/_moments/cdf_demographic_parity_moment.py
@@ -36,7 +36,7 @@ def __init__(self, loss, y_range, difference_bound=None, grids=[], grid_num=41):
         super().__init__()
         self.utility_parity = UtilityParity(difference_bound=difference_bound)
         self.loss = loss
-        self.objective = WeightedErrorRate(self.loss)
+        self.objective = WeightedErrorRate()
         self.grids = grids
         self.grid_num = grid_num
         self.y_range = y_range
diff --git a/fairlearn/reductions/_moments/weighted_error_rate.py b/fairlearn/reductions/_moments/weighted_error_rate.py
index 3d0add7c0..873c4448d 100644
--- a/fairlearn/reductions/_moments/weighted_error_rate.py
+++ b/fairlearn/reductions/_moments/weighted_error_rate.py
@@ -18,8 +18,8 @@ class WeightedErrorRate(ClassificationMoment):
 
     short_name = "Weighted Error Rate"
 
-    def __init__(self, loss):
-        super(WeightedErrorRate, self).__init__(loss)
+    def __init__(self):
+        super(WeightedErrorRate, self).__init__()
 
     '''for what we need here is augmented data. Hence to avoid unnecessary calculation, we use
     augmented data having been calculated in regression_moment here and directly return in