diff --git a/python/cudf/cudf/_lib/scalar.pyx b/python/cudf/cudf/_lib/scalar.pyx
index 6a78be000c9..a5945bc72f0 100644
--- a/python/cudf/cudf/_lib/scalar.pyx
+++ b/python/cudf/cudf/_lib/scalar.pyx
@@ -47,7 +47,7 @@ cdef class DeviceScalar:
 
     def __init__(self, value, dtype):
         """
-        cudf.Scalar: Type representing a scalar value on the device
+        Type representing an *immutable* scalar value on the device
 
         Parameters
         ----------
@@ -63,6 +63,7 @@ cdef class DeviceScalar:
         self._set_value(value, dtype)
 
     def _set_value(self, value, dtype):
+        # IMPORTANT: this should only ever be called from __init__
         valid = not _is_null_host_scalar(value)
 
         if pd.api.types.is_string_dtype(dtype):
@@ -128,9 +129,12 @@ cdef class DeviceScalar:
 
     def __repr__(self):
         if self.value is cudf.NA:
-            return f"Scalar({self.value}, {self.dtype.__repr__()})"
+            return (
+                f"{self.__class__.__name__}"
+                f"({self.value}, {self.dtype.__repr__()})"
+            )
         else:
-            return f"Scalar({self.value.__repr__()})"
+            return f"{self.__class__.__name__}({self.value.__repr__()})"
 
     @staticmethod
     cdef DeviceScalar from_unique_ptr(unique_ptr[scalar] ptr):
diff --git a/python/cudf/cudf/core/scalar.py b/python/cudf/cudf/core/scalar.py
index a3467e6fbe0..1e998ae37e2 100644
--- a/python/cudf/cudf/core/scalar.py
+++ b/python/cudf/cudf/core/scalar.py
@@ -56,7 +56,14 @@ def __init__(self, value, dtype=None):
         self._host_value = None
         self._host_dtype = None
         self._device_value = None
-        if isinstance(value, DeviceScalar):
+
+        if isinstance(value, Scalar):
+            if value._is_host_value_current:
+                self._host_value = value._host_value
+                self._host_dtype = value._host_dtype
+            else:
+                self._device_value = value._device_value
+        elif isinstance(value, DeviceScalar):
             self._device_value = value
         else:
             self._host_value, self._host_dtype = self._preprocess_host_value(
@@ -248,7 +255,10 @@ def __neg__(self):
     def __repr__(self):
         # str() fixes a numpy bug with NaT
         # https://github.com/numpy/numpy/issues/17552
-        return f"Scalar({str(self.value)}, dtype={self.dtype})"
+        return (
+            f"{self.__class__.__name__}"
+            f"({str(self.value)}, dtype={self.dtype})"
+        )
 
     def _binop_result_dtype_or_error(self, other, op):
         if op in {"__eq__", "__ne__", "__lt__", "__gt__", "__le__", "__ge__"}:
diff --git a/python/cudf/cudf/tests/test_scalar.py b/python/cudf/cudf/tests/test_scalar.py
index 003e46c7e0d..58115cecee7 100644
--- a/python/cudf/cudf/tests/test_scalar.py
+++ b/python/cudf/cudf/tests/test_scalar.py
@@ -289,3 +289,17 @@ def test_device_scalar_direct_construction(value):
         assert s.dtype == "object"
     else:
         assert s.dtype == dtype
+
+
+@pytest.mark.parametrize("value", SCALAR_VALUES)
+def test_construct_from_scalar(value):
+    value = cudf.utils.utils.to_cudf_compatible_scalar(value)
+    x = cudf.Scalar(value, value.dtype)
+    y = cudf.Scalar(x)
+    assert x.value == y.value or np.isnan(x.value) and np.isnan(y.value)
+
+    # check that this works:
+    y.device_value
+
+    x._is_host_value_current == y._is_host_value_current
+    x._is_device_value_current == y._is_device_value_current