diff --git a/soliket/bias/bias.py b/soliket/bias/bias.py
index c7d63aa1..5597de7c 100644
--- a/soliket/bias/bias.py
+++ b/soliket/bias/bias.py
@@ -41,7 +41,7 @@ class Bias(Theory):
     extra_args: Optional[dict]
     params: dict
 
-    enforce_types: bool = True
+    _enforce_types: bool = True
 
     _logz = np.linspace(-3, np.log10(1100), 150)
     _default_z_sampling = 10 ** _logz
@@ -99,7 +99,7 @@ class Linear_bias(Bias):
     Has one free parameter, :math:`b_\mathrm{lin}` (``b_lin``).
     """
 
-    enforce_types: bool = True
+    _enforce_types: bool = True
     params: dict
 
     def calculate(self, state: dict, want_derived: bool = True,
diff --git a/soliket/cash/cash.py b/soliket/cash/cash.py
index 64b41c8c..18e6abd2 100644
--- a/soliket/cash/cash.py
+++ b/soliket/cash/cash.py
@@ -11,7 +11,7 @@ class CashCLikelihood(Likelihood):
     name: str = "Cash-C"
     datapath: Optional[str] = None
 
-    enforce_types: bool = True
+    _enforce_types: bool = True
 
     def initialize(self):
         x, N = self._get_data()
diff --git a/soliket/ccl/ccl.py b/soliket/ccl/ccl.py
index 1b26254b..152d6f6b 100644
--- a/soliket/ccl/ccl.py
+++ b/soliket/ccl/ccl.py
@@ -91,7 +91,7 @@ class CCL(Theory):
     z: Union[float, List[float], np.ndarray]
     extra_args: Optional[dict]
 
-    enforce_types: bool = True
+    _enforce_types: bool = True
 
     _logz = np.linspace(-3, np.log10(1100), 150)
     _default_z_sampling = 10 ** _logz
diff --git a/soliket/cosmopower/cosmopower.py b/soliket/cosmopower/cosmopower.py
index f981f2c3..6fb261b0 100644
--- a/soliket/cosmopower/cosmopower.py
+++ b/soliket/cosmopower/cosmopower.py
@@ -110,7 +110,7 @@
 class CosmoPower(BoltzmannBase):
     """A CosmoPower Network wrapper for Cobaya."""
 
-    enforce_types: bool = True
+    _enforce_types: bool = True
 
     def initialize(self):
 
diff --git a/soliket/gaussian/gaussian.py b/soliket/gaussian/gaussian.py
index e9df199f..6b33c018 100644
--- a/soliket/gaussian/gaussian.py
+++ b/soliket/gaussian/gaussian.py
@@ -18,7 +18,7 @@ class GaussianLikelihood(Likelihood):
     ncovsims: Optional[int] = None
     provider: Provider
 
-    enforce_types: bool = True
+    _enforce_types: bool = True
 
     def initialize(self):
         x, y = self._get_data()
diff --git a/soliket/halo_model/halo_model.py b/soliket/halo_model/halo_model.py
index 97c49482..e350d76b 100644
--- a/soliket/halo_model/halo_model.py
+++ b/soliket/halo_model/halo_model.py
@@ -47,7 +47,7 @@ class HaloModel(Theory):
     z: Union[float, List[float], np.ndarray]
     extra_args: Optional[dict]
 
-    enforce_types: bool = True
+    _enforce_types: bool = True
 
     _logz = np.linspace(-3, np.log10(1100), 150)
     _default_z_sampling = 10**_logz
diff --git a/soliket/poisson/poisson.py b/soliket/poisson/poisson.py
index 997f5a4b..1e689bb1 100644
--- a/soliket/poisson/poisson.py
+++ b/soliket/poisson/poisson.py
@@ -10,7 +10,7 @@ class PoissonLikelihood(Likelihood):
     data_path: Optional[str] = None
     columns: Optional[List[str]] = None
 
-    enforce_types: bool = True
+    _enforce_types: bool = True
 
     def initialize(self):
         catalog = self._get_catalog()