BUG: Fix ma coercion list-of-ma-arrays if they do not cast to bool

There was a regression here due to force casting to bool, but if that
happens to fail (it does, but should not for strings). The mask
would just be dropped.

Of course masked arrays are held together by faith here, but its
a regression.

Closes gh-18551

numpy/ma/core.py

@@ -2859,8 +2859,9 @@ def __new__(cls, data=None, mask=nomask, dtype=None, copy=False,
             elif isinstance(data, (tuple, list)):
                 try:
                     # If data is a sequence of masked array
-                    mask = np.array([getmaskarray(np.asanyarray(m, dtype=mdtype))
-                                                    for m in data], dtype=mdtype)
+                    mask = np.array(
+                        [getmaskarray(np.asanyarray(m, dtype=_data.dtype))
+                         for m in data], dtype=mdtype)
                 except ValueError:
                     # If data is nested
                     mask = nomask

numpy/ma/tests/test_core.py

@@ -238,6 +238,25 @@ def test_creation_with_list_of_maskedarrays(self):
         assert_equal(data, [[0, 1, 2, 3, 4], [4, 3, 2, 1, 0]])
         assert_(data.mask is nomask)
 
+    def test_creation_with_list_of_maskedarrays_no_bool_cast(self):
+        # Tests the regression in gh-18551
+        masked_str = np.ma.masked_array(['a', 'b'], mask=[True, False])
+        normal_int = np.arange(2)
+        res = np.ma.asarray([masked_str, normal_int])
+        assert_array_equal(res.mask, [[True, False], [False, False]])
+        # Te above only failed due a long chain of oddity, try also with
+        # an object array that cannot be converted to bool always:
+        class NotBool():
+            def __bool__(self):
+                raise ValueError("not a bool!")
+        masked_obj = np.ma.masked_array([NotBool(), 'b'], mask=[True, False])
+        # Check that the NotBool actually fails like we would expect:
+        with pytest.raises(ValueError, match="not a bool!"):
+            np.asarray([masked_obj], dtype=bool)
+
+        res = np.ma.asarray([masked_obj, normal_int])
+        assert_array_equal(res.mask, [[True, False], [False, False]])
+
     def test_creation_from_ndarray_with_padding(self):
         x = np.array([('A', 0)], dtype={'names':['f0','f1'],
                                         'formats':['S4','i8'],