diff --git a/CHANGES.rst b/CHANGES.rst
index c589dccd29..b912f10ceb 100644
--- a/CHANGES.rst
+++ b/CHANGES.rst
@@ -47,6 +47,9 @@ outlier_detection
 
 - Add association id to ``outlier_i2d`` intermediate filenames. [#8418]
 
+- Pass the ``weight_type`` parameter to all resampling function calls so that
+  the default weighting can be overridden by the input step parameter. [#8290]
+
 pipeline
 --------
 
diff --git a/jwst/outlier_detection/outlier_detection.py b/jwst/outlier_detection/outlier_detection.py
index fc29873094..ef584132ec 100644
--- a/jwst/outlier_detection/outlier_detection.py
+++ b/jwst/outlier_detection/outlier_detection.py
@@ -113,7 +113,7 @@ def _convert_inputs(self):
                                               dq=self.inputs.dq[i])
                 image.meta = self.inputs.meta
                 image.wht = build_driz_weight(image,
-                                              weight_type='ivm',
+                                              weight_type=self.outlierpars['weight_type'],
                                               good_bits=bits)
                 self.input_models.append(image)
             self.converted = True
@@ -199,7 +199,7 @@ def do_detection(self):
             for i in range(len(self.input_models)):
                 drizzled_models[i].wht = build_driz_weight(
                     self.input_models[i],
-                    weight_type='ivm',
+                    weight_type=pars['weight_type'],
                     good_bits=pars['good_bits'])
 
         # Initialize intermediate products used in the outlier detection
diff --git a/jwst/outlier_detection/outlier_detection_scaled.py b/jwst/outlier_detection/outlier_detection_scaled.py
index a7252bd9af..e3b8c2cfcf 100644
--- a/jwst/outlier_detection/outlier_detection_scaled.py
+++ b/jwst/outlier_detection/outlier_detection_scaled.py
@@ -102,7 +102,7 @@ def do_detection(self):
         for image in self.input_models:
             image.wht = resample_utils.build_driz_weight(
                 image,
-                weight_type='ivm',
+                weight_type=pars['weight_type'],
                 good_bits=pars['good_bits']
             )
 
diff --git a/jwst/outlier_detection/outlier_detection_spec.py b/jwst/outlier_detection/outlier_detection_spec.py
index 1cc60db1c7..4adf2b4b06 100644
--- a/jwst/outlier_detection/outlier_detection_spec.py
+++ b/jwst/outlier_detection/outlier_detection_spec.py
@@ -88,7 +88,7 @@ def do_detection(self):
             for i in range(len(self.input_models)):
                 drizzled_models[i].wht = resample_utils.build_driz_weight(
                     self.input_models[i],
-                    weight_type='ivm',
+                    weight_type=pars['weight_type'],
                     good_bits=pars['good_bits'])
 
         # Initialize intermediate products used in the outlier detection
diff --git a/jwst/outlier_detection/outlier_detection_step.py b/jwst/outlier_detection/outlier_detection_step.py
index 077fdcf782..2c90435045 100644
--- a/jwst/outlier_detection/outlier_detection_step.py
+++ b/jwst/outlier_detection/outlier_detection_step.py
@@ -102,7 +102,8 @@ def process(self, input_data):
 
             # Setup outlier detection parameters
             pars = {
-                'weight_type': self.weight_type,
+                'weight_type': self.weight_type,  # for calling the resample step
+                'wht_type': self.weight_type,  # for calling the resample class directly
                 'pixfrac': self.pixfrac,
                 'kernel': self.kernel,
                 'fillval': self.fillval,