diff --git a/README.md b/README.md
index bf9e929..65def3b 100644
--- a/README.md
+++ b/README.md
@@ -198,20 +198,21 @@ client = TtdDatabricksClient.from_params(
 
 Provide your own [`DataClient`](https://github.com/thetradedesk/ttd-data-python/blob/main/src/ttd_data/sdk.py) instance to control the underlying HTTP transport directly.
 Use this when you need to configure options not exposed by `from_params()`, or to inject a mock in tests.
+The `DataClient` you pass in must carry your API token as `ttd_auth`; every request the SDK makes authenticates with it.
 
 ```python
 from ttd_data import DataClient
 from ttd_databricks_python.ttd_databricks import TtdDatabricksClient
 
-# Configure DataClient with custom HTTP settings.
+# Configure DataClient with your API token and custom HTTP settings.
 data_client = DataClient(
+    ttd_auth="<ttd-auth-token>",                      # your TTD platform API token
     server_url="https://custom-server.example.com",  # override default server URL
     timeout_ms=10000,                                 # request timeout in milliseconds
 )
 
 client = TtdDatabricksClient(
     data_api_client=data_client,
-    api_token="<ttd-auth-token>",
     spark=spark,  # optional; spark variable available from the Databricks notebook runtime
 )
 ```
@@ -456,15 +457,13 @@ from ttd_data.utils.retries import BackoffStrategy, RetryConfig
 from ttd_databricks_python.ttd_databricks import TtdDatabricksClient
 
 data_client = DataClient(
+    ttd_auth="<ttd-auth-token>",                      # your TTD platform API token
     server_url="https://custom-server.example.com",  # override default server URL
     timeout_ms=10000,                                 # request timeout in milliseconds
     retry_config=RetryConfig("backoff", BackoffStrategy(1000, 60000, 1.5, 3600000), True),  # custom retry config
 )
 
-client = TtdDatabricksClient(
-    data_api_client=data_client,
-    api_token="<ttd-auth-token>",
-)
+client = TtdDatabricksClient(data_api_client=data_client)
 ```
 
 In batch processing mode, a `DataClient` singleton is maintained per Spark worker process to enable HTTP connection reuse across batches, reducing overhead during distributed execution.
diff --git a/pyproject.toml b/pyproject.toml
index ba08aed..a04f57a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "ttd-databricks"
-version = "0.5.0"
+version = "0.6.0"
 description = "Client implementation and helper functions for integrating with the TTD Databricks services."
 readme = "README.md"
 requires-python = ">=3.10"
@@ -15,7 +15,7 @@ authors = [
 ]
 
 dependencies = [
-    "ttd-data>=0.2.6,<0.3.0",
+    "ttd-data>=0.3.0,<0.4.0",
     "pandas>=1.0.5",
     "pyarrow>=4.0.0",
     "setuptools>=63.4.1",
@@ -54,6 +54,7 @@ select = [
 ]
 ignore = [
     "UP045",  # prefer Optional[X] over X | None
+    "UP007",  # prefer Union[X, Y] over X | Y
 ]
 
 [tool.ruff.lint.isort]
diff --git a/tests/unit/test_batch_process_early_exit.py b/tests/unit/test_batch_process_early_exit.py
index 04c1085..aaafcc8 100644
--- a/tests/unit/test_batch_process_early_exit.py
+++ b/tests/unit/test_batch_process_early_exit.py
@@ -34,7 +34,6 @@
 def _make_client(spark: SparkSession) -> TtdDatabricksClient:
     return TtdDatabricksClient(
         data_api_client=MagicMock(spec=DataClient),
-        api_token="test-token",
         spark=spark,
     )
 
diff --git a/tests/unit/test_call_api.py b/tests/unit/test_call_api.py
index 0269661..6b7ec5c 100644
--- a/tests/unit/test_call_api.py
+++ b/tests/unit/test_call_api.py
@@ -30,7 +30,7 @@
 
 
 def _make_client() -> TtdDatabricksClient:
-    return TtdDatabricksClient(data_api_client=MagicMock(spec=DataClient), api_token="test-token")
+    return TtdDatabricksClient(data_api_client=MagicMock(spec=DataClient))
 
 
 def _make_rows(*dicts: dict[str, Any]) -> list[MagicMock]:
diff --git a/tests/unit/test_client_helpers.py b/tests/unit/test_client_helpers.py
index 30200d4..a88ea07 100644
--- a/tests/unit/test_client_helpers.py
+++ b/tests/unit/test_client_helpers.py
@@ -19,7 +19,6 @@
 def _make_client(**kwargs) -> TtdDatabricksClient:  # type: ignore[no-untyped-def]
     return TtdDatabricksClient(
         data_api_client=MagicMock(spec=DataClient),
-        api_token="test-token",
         **kwargs,
     )
 
diff --git a/tests/unit/test_process_partitions.py b/tests/unit/test_process_partitions.py
index 3805292..ec79dea 100644
--- a/tests/unit/test_process_partitions.py
+++ b/tests/unit/test_process_partitions.py
@@ -17,11 +17,12 @@
 from collections.abc import Iterator
 from http import HTTPStatus
 from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from typing import Optional
 
 import pytest
 from pyspark.sql import SparkSession
 from pyspark.sql.types import StringType, StructField, StructType, TimestampType
-from ttd_data import ClientConfig
+from ttd_data import DataClient
 
 from ttd_databricks_python.ttd_databricks.batching import process_partitions
 from ttd_databricks_python.ttd_databricks.contexts import AdvertiserContext
@@ -29,16 +30,15 @@
 
 pytestmark = pytest.mark.spark
 
-# Pinned so request counts stay exact: retry_config=None leaves the SDK's retry wrapper
-# off, so each batch makes exactly one call even when the stub returns a retryable 5xx.
+_TOKEN = "not-a-real-token"
+
+# Snapshotted off a real DataClient rather than hand-built, so the test tracks whatever
+# fields ClientConfig carries in the installed ttd-data.
+# retry_config=None leaves the SDK's retry wrapper off, keeping request counts exact: each
+# batch makes exactly one call even when the stub returns a retryable 5xx.
 # Shared by both tests — workers cache one DataClient per process, so a differing config
 # in a second test would be silently ignored.
-_NO_RETRY_CLIENT_CONFIG = ClientConfig(
-    server_url=None,
-    retry_config=None,
-    timeout_ms=10_000,
-    uid2_config=None,
-)
+_NO_RETRY_CLIENT_CONFIG = DataClient(ttd_auth=_TOKEN, retry_config=None, timeout_ms=10_000).config
 
 
 class _StubHandler(BaseHTTPRequestHandler):
@@ -46,6 +46,7 @@ class _StubHandler(BaseHTTPRequestHandler):
 
     status_code = 500
     request_count = 0
+    auth_headers: list[Optional[str]] = []
     # ThreadingHTTPServer handles each request on its own thread; `+= 1` is a
     # non-atomic read-modify-write, so guard it rather than relying on the spark
     # fixture staying single-threaded.
@@ -56,10 +57,12 @@ def configure(cls, status_code: int) -> None:
         with cls.counter_lock:
             cls.status_code = status_code
             cls.request_count = 0
+            cls.auth_headers = []
 
     def do_POST(self) -> None:  # noqa: N802 — required by stdlib BaseHTTPRequestHandler
         with type(self).counter_lock:
             type(self).request_count += 1
+            type(self).auth_headers.append(self.headers.get("TTD-Auth"))
         body = b'{"Message":"forced error for test"}'
         self.send_response(type(self).status_code)
         self.send_header("Content-Type", "application/json")
@@ -112,7 +115,6 @@ def test_mapinpandas_wires_up_and_round_trips(spark: SparkSession, stub_server:
         df=input_df,
         batch_size=3,
         output_schema=output_schema,
-        api_token="not-a-real-token",
         context=context,
         parallelism=2,
         client_config=_NO_RETRY_CLIENT_CONFIG,
@@ -127,6 +129,9 @@ def test_mapinpandas_wires_up_and_round_trips(spark: SparkSession, stub_server:
     assert result_df.schema.fieldNames() == output_schema.fieldNames()
     # 4. Input column values survive Arrow → pandas → dict → pandas → Arrow round-trip.
     assert {row["id_value"] for row in result_rows} == set(input_ids)
+    # 5. The worker's rebuilt DataClient authenticates: ttd_auth travels in the client_config
+    #    snapshot, not as a separate per-call argument.
+    assert set(_StubHandler.auth_headers) == {_TOKEN}
 
 
 @pytest.mark.parametrize(
@@ -149,7 +154,6 @@ def test_401_and_403_stop_partition_without_failing_job(spark: SparkSession, stu
         df=input_df,
         batch_size=3,
         output_schema=output_schema,
-        api_token="not-a-real-token",
         context=context,
         parallelism=1,
         client_config=_NO_RETRY_CLIENT_CONFIG,
@@ -182,7 +186,6 @@ def test_other_4xx_fails_only_its_own_batch(spark: SparkSession, stub_server: st
         df=input_df,
         batch_size=3,
         output_schema=output_schema,
-        api_token="not-a-real-token",
         context=context,
         parallelism=1,
         client_config=_NO_RETRY_CLIENT_CONFIG,
diff --git a/tests/unit/test_push_data.py b/tests/unit/test_push_data.py
index 58233bf..21befaf 100644
--- a/tests/unit/test_push_data.py
+++ b/tests/unit/test_push_data.py
@@ -32,7 +32,6 @@
 def _make_client(spark: SparkSession) -> TtdDatabricksClient:
     return TtdDatabricksClient(
         data_api_client=MagicMock(spec=DataClient),
-        api_token="test-token",
         spark=spark,
     )
 
diff --git a/tests/unit/test_uid2_resolutions.py b/tests/unit/test_uid2_resolutions.py
index 295f973..10dbd8b 100644
--- a/tests/unit/test_uid2_resolutions.py
+++ b/tests/unit/test_uid2_resolutions.py
@@ -306,7 +306,7 @@ def test_raises_with_alter_table_hint_when_column_missing(self) -> None:
 
 
 def _make_client() -> TtdDatabricksClient:
-    return TtdDatabricksClient(data_api_client=MagicMock(spec=DataClient), api_token="test-token")
+    return TtdDatabricksClient(data_api_client=MagicMock(spec=DataClient))
 
 
 def _make_rows(*dicts: dict) -> list[MagicMock]:
@@ -420,4 +420,5 @@ def test_batch_process_config_is_derived_from_data_api_client() -> None:
 
     assert client._data_api_client.config.uid2_config is uid2_cfg
     assert client._data_api_client.config.retry_config is retry_cfg
+    assert client._data_api_client.config.ttd_auth == "tok"
 
diff --git a/ttd_databricks_python/ttd_databricks/batching.py b/ttd_databricks_python/ttd_databricks/batching.py
index dfdedc0..e9716e6 100644
--- a/ttd_databricks_python/ttd_databricks/batching.py
+++ b/ttd_databricks_python/ttd_databricks/batching.py
@@ -39,11 +39,10 @@ def process_partitions(
     df: DataFrame,
     batch_size: int,
     output_schema: StructType,
-    api_token: str,
     context: TTDContext,
+    client_config: ClientConfig,
     parallelism: Optional[int] = None,
     data_load_trace_id: Optional[str] = None,
-    client_config: Optional[ClientConfig] = None,
 ) -> DataFrame:
     """Process all rows through the API using a single mapInPandas pass.
 
@@ -57,7 +56,7 @@ def process_partitions(
     on server responses. Falls back to _DEFAULT_PARALLELISM on serverless / Spark
     Connect where sparkContext is unavailable.
 
-    client_config is a snapshot of the driver DataClient's settings (server_url,
+    client_config is a snapshot of the driver DataClient's settings (ttd_auth, server_url,
     retry_config, timeout_ms, uid2_config), used to rebuild an equivalent DataClient
     per worker.
 
@@ -81,7 +80,7 @@ def partition_to_results(pandas_df_iter: Iterable[pd.DataFrame]) -> Iterator[pd.
         import pandas as pd
         from ttd_data import DataClient
 
-        from ttd_databricks_python.ttd_databricks.constants import ABORTED_ERROR_CODE, DEFAULT_RETRY_CONFIG
+        from ttd_databricks_python.ttd_databricks.constants import ABORTED_ERROR_CODE
         from ttd_databricks_python.ttd_databricks.utils import (
             attach_resolutions,
             classify_failure,
@@ -92,11 +91,9 @@ def partition_to_results(pandas_df_iter: Iterable[pd.DataFrame]) -> Iterator[pd.
         global _worker_client
         if _worker_client is None:
             # Workers rebuild the client from the picklable client_config snapshot;
-            # DataClient itself can't be cloudpickled.
-            if client_config is None:
-                _worker_client = DataClient(timeout_ms=10_000, retry_config=DEFAULT_RETRY_CONFIG)
-            else:
-                _worker_client = DataClient.from_config(client_config)
+            # DataClient itself can't be cloudpickled. The snapshot carries ttd_auth, so the
+            # rebuilt client authenticates exactly as the driver's client does.
+            _worker_client = DataClient.from_config(client_config)
         client = _worker_client
         handler = importlib.import_module(handler_module)
 
@@ -139,9 +136,7 @@ def abort(error_code: str, error_message: str) -> pd.DataFrame:
             try:
                 items = handler.build_items(batch_rows)
                 raw_pii_ids_per_row = handler.collect_raw_pii_ids_per_row(batch_rows)
-                failed_lines, identity_resolutions = handler.call_api(
-                    client, context, items, api_token, data_load_trace_id
-                )
+                failed_lines, identity_resolutions = handler.call_api(client, context, items, data_load_trace_id)
                 row_results = parse_failed_lines(failed_lines, len(batch_rows))
                 attach_resolutions(row_results, raw_pii_ids_per_row, identity_resolutions)
             except Exception as exc:
diff --git a/ttd_databricks_python/ttd_databricks/handlers/advertiser.py b/ttd_databricks_python/ttd_databricks/handlers/advertiser.py
index bc8fe1d..8375592 100644
--- a/ttd_databricks_python/ttd_databricks/handlers/advertiser.py
+++ b/ttd_databricks_python/ttd_databricks/handlers/advertiser.py
@@ -53,7 +53,6 @@ def call_api(
     client: DataClient,
     context: AdvertiserContext,
     items: list[AdvertiserDataItem],
-    api_token: str,
     data_load_trace_id: Optional[str] = None,
 ) -> tuple[list[Any], dict[str, UID2Resolution]]:
     """Call ingest_advertiser_data. Returns (failed_lines, identity_resolutions).
@@ -72,7 +71,6 @@ def call_api(
     try:
         response = client.advertiser.ingest_advertiser_data(
             advertiser_id=context.advertiser_id,
-            ttd_auth=api_token,
             data_provider_id=context.data_provider_id if context.data_provider_id is not None else UNSET,
             items=items,
             data_load_trace_id=data_load_trace_id if data_load_trace_id is not None else UNSET,
diff --git a/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_advertiser.py b/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_advertiser.py
index 74a1aa2..adc870b 100644
--- a/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_advertiser.py
+++ b/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_advertiser.py
@@ -37,7 +37,6 @@ def call_api(
     client: DataClient,
     context: DeletionOptOutAdvertiserContext,
     items: list[PartnerDsrDataItem],
-    api_token: str,
     data_load_trace_id: Optional[str] = None,
 ) -> tuple[list[Any], dict[str, UID2Resolution]]:
     """Call data_subject_request_advertiser_data.
@@ -49,7 +48,6 @@ def call_api(
 
     try:
         response = client.deletion_opt_out.data_subject_request_advertiser_data(
-            ttd_auth=api_token,
             advertiser_id=context.advertiser_id,
             data_provider_id=context.data_provider_id if context.data_provider_id is not None else UNSET,
             items=items,
diff --git a/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_merchant.py b/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_merchant.py
index d96ca69..345769d 100644
--- a/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_merchant.py
+++ b/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_merchant.py
@@ -37,7 +37,6 @@ def call_api(
     client: DataClient,
     context: DeletionOptOutMerchantContext,
     items: list[PartnerDsrDataItem],
-    api_token: str,
     data_load_trace_id: Optional[str] = None,
 ) -> tuple[list[Any], dict[str, UID2Resolution]]:
     """Call data_subject_request_merchant_data.
@@ -49,7 +48,6 @@ def call_api(
 
     try:
         response = client.deletion_opt_out.data_subject_request_merchant_data(
-            ttd_auth=api_token,
             merchant_id=context.merchant_id,
             items=items,
             data_load_trace_id=data_load_trace_id if data_load_trace_id is not None else UNSET,
diff --git a/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_thirdparty.py b/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_thirdparty.py
index 25aa0ae..97e544c 100644
--- a/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_thirdparty.py
+++ b/ttd_databricks_python/ttd_databricks/handlers/deletion_optout_thirdparty.py
@@ -37,7 +37,6 @@ def call_api(
     client: DataClient,
     context: DeletionOptOutThirdPartyContext,
     items: list[PartnerDsrDataItem],
-    api_token: str,
     data_load_trace_id: Optional[str] = None,
 ) -> tuple[list[Any], dict[str, UID2Resolution]]:
     """Call data_subject_request_third_party_data.
@@ -49,7 +48,6 @@ def call_api(
 
     try:
         response = client.deletion_opt_out.data_subject_request_third_party_data(
-            ttd_auth=api_token,
             data_provider_id=context.data_provider_id,
             brand_id=context.brand_id if context.brand_id is not None else UNSET,
             items=items,
diff --git a/ttd_databricks_python/ttd_databricks/handlers/offline_conversion.py b/ttd_databricks_python/ttd_databricks/handlers/offline_conversion.py
index 759afb9..c6779ec 100644
--- a/ttd_databricks_python/ttd_databricks/handlers/offline_conversion.py
+++ b/ttd_databricks_python/ttd_databricks/handlers/offline_conversion.py
@@ -116,7 +116,6 @@ def call_api(
     client: DataClient,
     context: OfflineConversionContext,
     items: list[OfflineConversionDataItem],
-    api_token: str,
     data_load_trace_id: Optional[str] = None,
 ) -> tuple[list[Any], dict[str, UID2Resolution]]:
     """Call ingest_offline_conversion_data. Returns (failed_lines, identity_resolutions).
@@ -136,7 +135,6 @@ def call_api(
 
     try:
         response = client.offline_conversion.ingest_offline_conversion_data(
-            ttd_auth=api_token,
             data_provider_id=context.data_provider_id,
             user_id_array_metadata_format=["type", "id"] if has_user_id_array else UNSET,
             items=items,
diff --git a/ttd_databricks_python/ttd_databricks/handlers/third_party.py b/ttd_databricks_python/ttd_databricks/handlers/third_party.py
index a3fefbb..c679311 100644
--- a/ttd_databricks_python/ttd_databricks/handlers/third_party.py
+++ b/ttd_databricks_python/ttd_databricks/handlers/third_party.py
@@ -53,7 +53,6 @@ def call_api(
     client: DataClient,
     context: ThirdPartyContext,
     items: list[ThirdPartyDataItem],
-    api_token: str,
     data_load_trace_id: Optional[str] = None,
 ) -> tuple[list[Any], dict[str, UID2Resolution]]:
     """Call ingest_third_party_data. Returns (failed_lines, identity_resolutions).
@@ -71,7 +70,6 @@ def call_api(
 
     try:
         response = client.third_party.ingest_third_party_data(
-            ttd_auth=api_token,
             data_provider_id=context.data_provider_id,
             items=items,
             is_user_id_already_hashed=context.is_user_id_already_hashed,
diff --git a/ttd_databricks_python/ttd_databricks/ttd_client.py b/ttd_databricks_python/ttd_databricks/ttd_client.py
index e24e086..cb8bc1a 100644
--- a/ttd_databricks_python/ttd_databricks/ttd_client.py
+++ b/ttd_databricks_python/ttd_databricks/ttd_client.py
@@ -7,7 +7,8 @@
 
 # ttd-data is the external SDK for the TTD Data API.
 # Install via: pip install ttd-data
-# DataClient is the main HTTP client. The TTD-Auth token is passed per API call.
+# DataClient is the main HTTP client. It is given the TTD-Auth token when it is constructed,
+# and authenticates every request the SDK makes with it.
 from ttd_data import DataClient
 from ttd_data.types import OptionalNullable
 from ttd_data.uid2 import UID2Config
@@ -31,7 +32,7 @@ class TtdDatabricksClient:
     Supports two usage patterns:
 
     1. Dependency Injection (recommended for testing):
-       client = TtdDatabricksClient(data_api_client=DataClient(), api_token="...")
+       client = TtdDatabricksClient(data_api_client=DataClient(ttd_auth="..."))
 
     2. Factory method (convenience for notebooks):
        client = TtdDatabricksClient.from_params(api_token="...")
@@ -40,7 +41,6 @@ class TtdDatabricksClient:
     def __init__(
         self,
         data_api_client: DataClient,
-        api_token: str,
         spark: Optional[SparkSession] = None,
     ) -> None:
         """
@@ -49,16 +49,23 @@ def __init__(
         Auto-detect spark session unless explicitly provided.
 
         Dependency Injection pattern:
-        - data_api_client: Required. Injected DataClient instance (from ttd-data package).
-          `batch_process` rebuilds an equivalent DataClient per worker from
-          `data_api_client.config` — a single place to configure uid2/retry settings.
-        - api_token: Required. TTD-Auth token passed to each API call for authentication.
+        - data_api_client: Required. Injected DataClient instance (from ttd-data package),
+          built with `ttd_auth` set to your TTD API token. `batch_process` rebuilds an
+          equivalent DataClient per worker from `data_api_client.config` — a single place
+          to configure the token and the uid2/retry settings.
 
         Note: DataClient is from the external ttd-data package.
         For factory pattern (creating clients from tokens), use `from_params()` class method.
         """
+        from ttd_databricks_python.ttd_databricks.exceptions import TTDConfigurationError
+
+        if data_api_client.config.ttd_auth is None:
+            raise TTDConfigurationError(
+                "data_api_client was created without a TTD API token. "
+                'Build it as DataClient(ttd_auth="<your-token>"), or use TtdDatabricksClient.from_params().'
+            )
+
         self._data_api_client = data_api_client
-        self._api_token = api_token
         self._spark = spark
 
     @classmethod
@@ -88,12 +95,13 @@ def from_params(
         Returns: TtdDatabricksClient instance with internally created DataClient.
         """
         data_api_client = DataClient(
+            ttd_auth=api_token,
             uid2_config=uid2_config,
             retry_config=retry_config,
             server_url=server_url,
             timeout_ms=timeout_ms,
         )
-        return cls(data_api_client=data_api_client, api_token=api_token, spark=spark)
+        return cls(data_api_client=data_api_client, spark=spark)
 
     # ------------------------------------------------------------------
     # Ad hoc mode
@@ -248,14 +256,13 @@ def batch_process(
         output_schema = get_output_schema(df.schema)
         self._validate_output_table_schema(spark, output_table, output_schema)
         output_df = process_partitions(
-            df,
-            batch_size,
-            output_schema,
-            self._api_token,
-            context,
-            parallelism,
-            data_load_trace_id,
-            self._data_api_client.config,
+            df=df,
+            batch_size=batch_size,
+            output_schema=output_schema,
+            context=context,
+            client_config=self._data_api_client.config,
+            parallelism=parallelism,
+            data_load_trace_id=data_load_trace_id,
         )
 
         output_df.write.format("delta").mode("append").saveAsTable(output_table)
@@ -466,7 +473,7 @@ def fail_all(error_code: str, error_message: str) -> list[dict[str, Any]]:
             items = handler.build_items(rows_data)
             raw_pii_ids_per_row = handler.collect_raw_pii_ids_per_row(rows_data)
             failed_lines, identity_resolutions = handler.call_api(
-                self._data_api_client, context, items, self._api_token, data_load_trace_id
+                self._data_api_client, context, items, data_load_trace_id
             )
             results = parse_failed_lines(failed_lines, len(rows))
             attach_resolutions(results, raw_pii_ids_per_row, identity_resolutions)