diff --git a/c/tskit/trees.c b/c/tskit/trees.c
index f51a4a0333..0ec70c7687 100644
--- a/c/tskit/trees.c
+++ b/c/tskit/trees.c
@@ -2834,9 +2834,6 @@ tsk_treeseq_update_branch_afs(const tsk_treeseq_t *self, tsk_id_t u, double righ
     }
 
     if (0 < all_samples && all_samples < self->num_samples) {
-        if (!polarised) {
-            x *= 0.5;
-        }
         afs_size = result_dims[num_sample_sets];
         afs = result + afs_size * window_index;
         for (k = 0; k < num_sample_sets; k++) {
diff --git a/python/tests/test_tree_stats.py b/python/tests/test_tree_stats.py
index 99e8e11c55..a272c4f8cf 100644
--- a/python/tests/test_tree_stats.py
+++ b/python/tests/test_tree_stats.py
@@ -1,6 +1,6 @@
 # MIT License
 #
-# Copyright (c) 2018-2023 Tskit Developers
+# Copyright (c) 2018-2024 Tskit Developers
 # Copyright (C) 2016 University of Oxford
 #
 # Permission is hereby granted, free of charge, to any person obtaining a copy
@@ -3395,6 +3395,13 @@ def foldit(A):
     return B
 
 
+def fold_windowed(X):
+    Y = np.zeros(X.shape)
+    for k in range(X.shape[0]):
+        Y[k] = foldit(X[k])
+    return Y
+
+
 class TestFold:
     """
     Tests for the fold operation used in the AFS.
@@ -3432,6 +3439,29 @@ def test_examples(self):
         Ef = np.array([8.0, 8.0, 8.0, 8.0, 4.0, 0.0, 0.0, 0.0, 0.0])
         assert np.all(foldit(E) == Ef)
 
+    def test_branch_folded(self):
+        ts = msprime.sim_ancestry(10, random_seed=1, sequence_length=10)
+        folded = ts.allele_frequency_spectrum(
+            windows=[0, 5, 8, 9, 10], mode="branch", polarised=False
+        )
+        unfolded = ts.allele_frequency_spectrum(
+            windows=[0, 5, 8, 9, 10], mode="branch", polarised=True
+        )
+        assert np.allclose(fold_windowed(unfolded), folded)
+
+    def test_site_folded(self):
+        ts = msprime.sim_ancestry(10, random_seed=1, sequence_length=10)
+        ts = msprime.sim_mutations(ts, rate=1, random_seed=1, discrete_genome=False)
+        for s in ts.sites():
+            assert len(s.mutations) == 1
+        folded = ts.allele_frequency_spectrum(
+            windows=[0, 5, 8, 9, 10], mode="site", polarised=False, span_normalise=False
+        )
+        unfolded = ts.allele_frequency_spectrum(
+            windows=[0, 5, 8, 9, 10], mode="site", polarised=True, span_normalise=False
+        )
+        assert np.allclose(fold_windowed(unfolded), folded)
+
 
 def naive_site_allele_frequency_spectrum(
     ts, sample_sets, windows=None, polarised=False, span_normalise=True
@@ -3513,11 +3543,9 @@ def naive_branch_allele_frequency_spectrum(
                     if 0 < t.num_samples(node) < ts.num_samples:
                         x = [tree.num_tracked_samples(node) for tree in trees]
                         # Note x must be a tuple for indexing to work
-                        if polarised:
-                            S[tuple(x)] += t.branch_length(node) * tr_len
-                        else:
+                        if not polarised:
                             x = fold(x, out_dim)
-                            S[tuple(x)] += 0.5 * t.branch_length(node) * tr_len
+                        S[tuple(x)] += t.branch_length(node) * tr_len
 
             # Advance the trees
             more = [tree.next() for tree in trees]
@@ -3582,7 +3610,6 @@ def update_result(window_index, u, right):
             c = count[u, :num_sample_sets]
             if not polarised:
                 c = fold(c, out_dim)
-                x *= 0.5
             index = tuple([window_index] + list(c))
             result[index] += x
         last_update[u] = right
@@ -3893,8 +3920,6 @@ def verify(self, ts):
                     polarised=polarised,
                     span_normalise=True,
                 )
-                if not polarised:
-                    afs *= 2
                 afs_sum = [np.sum(window) for window in afs]
                 self.assertArrayAlmostEqual(afs_sum, tbl)