diff --git a/app/api/search.py b/app/api/search.py
index d9a3235..a0e8f54 100644
--- a/app/api/search.py
+++ b/app/api/search.py
@@ -185,19 +185,33 @@ async def search(
                 + (" (bg triggered)" if triggered else " (bg inflight)")
             )
 
-    # Phase 2.2: multilingual vector search 활성 조건
+    # Phase 2.2: multilingual vector search 활성 조건 (보수적)
     #   - cache hit + analyzer_tier == "analyzed" (≥0.85 고신뢰)
     #   - normalized_queries 2개 이상 (lang 다양성 있음)
-    # 그 외 케이스는 기존 single-query search_vector 그대로 사용 (회귀 0).
+    #   - domain_hint == "news" 또는 language_scope == "global"
+    #   ↑ 1차 측정 결과: document 도메인에서 multilingual이 natural_language_ko
+    #     -0.10 악화시킴. 영어 번역이 한국어 법령 검색에서 noise로 작용.
+    #     news / global 영역에서만 multilingual 활성 (news_crosslingual +0.10 개선 확인).
     use_multilingual: bool = False
     normalized_queries: list[dict] = []
     if analyzer_cache_hit and analyzer_tier == "analyzed" and query_analysis:
-        raw_nq = query_analysis.get("normalized_queries") or []
-        if isinstance(raw_nq, list) and len(raw_nq) >= 2:
-            normalized_queries = [nq for nq in raw_nq if isinstance(nq, dict) and nq.get("text")]
-            if len(normalized_queries) >= 2:
-                use_multilingual = True
-                notes.append(f"multilingual langs={[nq.get('lang') for nq in normalized_queries]}")
+        domain_hint = query_analysis.get("domain_hint", "mixed")
+        language_scope = query_analysis.get("language_scope", "limited")
+        is_multilingual_candidate = (
+            domain_hint == "news" or language_scope == "global"
+        )
+        if is_multilingual_candidate:
+            raw_nq = query_analysis.get("normalized_queries") or []
+            if isinstance(raw_nq, list) and len(raw_nq) >= 2:
+                normalized_queries = [
+                    nq for nq in raw_nq if isinstance(nq, dict) and nq.get("text")
+                ]
+                if len(normalized_queries) >= 2:
+                    use_multilingual = True
+                    notes.append(
+                        f"multilingual langs={[nq.get('lang') for nq in normalized_queries]}"
+                        f" hint={domain_hint}/{language_scope}"
+                    )
 
     if mode == "vector":
         t0 = time.perf_counter()