diff --git a/src/vivarium/framework/results/context.py b/src/vivarium/framework/results/context.py
index 317867dbd..f7d23d0a5 100644
--- a/src/vivarium/framework/results/context.py
+++ b/src/vivarium/framework/results/context.py
@@ -5,7 +5,7 @@
 """
 
 from collections import defaultdict
-from typing import Any, Callable, Generator, List, Optional, Tuple, Type, Union
+from typing import Callable, Generator, List, Optional, Tuple, Type, Union
 
 import pandas as pd
 from pandas.core.groupby.generic import DataFrameGroupBy
diff --git a/src/vivarium/framework/results/interface.py b/src/vivarium/framework/results/interface.py
index 7ed8979b6..25eb9264d 100644
--- a/src/vivarium/framework/results/interface.py
+++ b/src/vivarium/framework/results/interface.py
@@ -8,7 +8,7 @@
 to a simulation.
 """
 
-from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Union
+from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Union
 
 import pandas as pd
 
diff --git a/src/vivarium/framework/results/manager.py b/src/vivarium/framework/results/manager.py
index ae052744e..25807899c 100644
--- a/src/vivarium/framework/results/manager.py
+++ b/src/vivarium/framework/results/manager.py
@@ -6,7 +6,7 @@
 
 from collections import defaultdict
 from enum import Enum
-from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
+from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Tuple, Union
 
 import pandas as pd
 
diff --git a/src/vivarium/framework/results/observation.py b/src/vivarium/framework/results/observation.py
index 6b1fb8255..d31062167 100644
--- a/src/vivarium/framework/results/observation.py
+++ b/src/vivarium/framework/results/observation.py
@@ -75,7 +75,7 @@ def observe(
         df: Union[pd.DataFrame, DataFrameGroupBy],
         stratifications: Optional[tuple[str, ...]],
     ) -> Optional[pd.DataFrame]:
-        """Determine whether to observe the given event and, if so, gather the results."""
+        # """Determine whether to observe the given event and, if so, gather the results."""
         if not self.to_observe(event):
             return None
         else:
diff --git a/src/vivarium/framework/results/stratification.py b/src/vivarium/framework/results/stratification.py
index c9ec7e279..765a047ac 100644
--- a/src/vivarium/framework/results/stratification.py
+++ b/src/vivarium/framework/results/stratification.py
@@ -5,7 +5,7 @@
 """
 
 from dataclasses import dataclass
-from typing import Any, Callable, List, Optional, Union
+from typing import Callable, List, Optional, Union
 
 import pandas as pd
 from pandas.api.types import CategoricalDtype
@@ -24,27 +24,6 @@ class Stratification:
 
     This class includes a :meth:`stratify <stratify>` method that produces an
     output column by calling the mapper on the source columns.
-
-    Attributes
-    ----------
-    name
-        Name of the stratification.
-    sources
-        A list of the columns and values needed as input for the `mapper`.
-    categories
-        Exhaustive list of all possible stratification values.
-    excluded_categories
-        List of possible stratification values to exclude from results processing.
-        If None (the default), will use exclusions as defined in the configuration.
-    mapper
-            A callable that maps the columns and value pipelines specified by the
-            `requires_columns` and `requires_values` arguments to the stratification
-            categories. It can either map the entire population or an individual
-            simulant. A simulation will fail if the `mapper` ever produces an invalid
-            value.
-    is_vectorized
-        True if the `mapper` function will map the entire population, and False
-        if it will only map a single simulant.
     """
 
     name: str