feat(governance): enforce fail-closed verification, handle shortfall edge cases, pass 23/23 tests

test_multiplatform_ranking.py

@@ -377,4 +377,82 @@ def test_publication_eligibility_gates(dataset):
     # 4. Check ranks are strictly unique and consecutive 1 to N
     ranks = gated["hiffi_xp_published_rank"].sort_values().tolist()
     expected_ranks = list(range(1, len(gated) + 1))
-    assert ranks == expected_ranks, "Published ranks contain gaps or duplicates."
+    assert ranks == expected_ranks, "Published ranks contain gaps or duplicates."
+
+def test_publication_gate_blocks_unverified_identity():
+    """Confirms that UNCERTAIN_NEEDS_REVIEW status does not count toward evidence tiers."""
+    engine = HIFFIRankingEngine()
+    test_df = pd.DataFrame([
+        {
+            "name": "Artist Pending Verification",
+            "production_hiffi_score": 95.0,
+            "spotify_monthly_listeners": 40_000_000,
+            "instagram_followers": 20_000_000,
+            "instagram_verification_status": "UNCERTAIN_NEEDS_REVIEW",
+            "hiffi_xp_score": 96.0,
+            "hiffi_xp_rank": 1
+        },
+        {
+            "name": "Artist Fully Verified",
+            "production_hiffi_score": 90.0,
+            "spotify_monthly_listeners": 35_000_000,
+            "instagram_followers": 15_000_000,
+            "instagram_verification_status": "AUTOMATED_VERIFIED",
+            "hiffi_xp_score": 91.0,
+            "hiffi_xp_rank": 2
+        }
+    ])
+
+    gated = engine.apply_publication_eligibility_gates(test_df)
+    pending_row = gated[gated["name"] == "Artist Pending Verification"].iloc[0]
+    verified_row = gated[gated["name"] == "Artist Fully Verified"].iloc[0]
+
+    assert pending_row["platform_evidence_tier"] == 2
+    assert verified_row["platform_evidence_tier"] == 3
+
+
+def test_publication_gate_missing_column_fails_closed():
+    """Confirms that omitting the verification column fails closed (gives 0 IG credit)."""
+    engine = HIFFIRankingEngine()
+    test_df = pd.DataFrame([
+        {
+            "name": "Artist No Status Column",
+            "production_hiffi_score": 95.0,
+            "spotify_monthly_listeners": 40_000_000,
+            "instagram_followers": 20_000_000,
+            "hiffi_xp_score": 96.0,
+            "hiffi_xp_rank": 1
+        }
+    ])
+
+    gated = engine.apply_publication_eligibility_gates(test_df)
+    assert gated.loc[0, "platform_evidence_tier"] == 2
+
+
+def test_publication_gate_zero_multiplatform_cohort():
+    """Confirms an entirely Tier 1 cohort produces consecutive ranks and flags an audited shortfall."""
+    engine = HIFFIRankingEngine()
+
+    records = [
+        {
+            "name": f"Solo Artist {i+1}",
+            "production_hiffi_score": 85.0 - i,
+            "spotify_monthly_listeners": np.nan,
+            "instagram_followers": np.nan,
+            "instagram_verification_status": "UNVERIFIED",
+            "hiffi_xp_score": 80.0 - i,
+            "hiffi_xp_rank": i + 1
+        }
+        for i in range(25)
+    ]
+
+    tier1_df = pd.DataFrame(records)
+    gated, audit = engine.apply_publication_eligibility_gates(tier1_df, return_metadata=True)
+
+    # Must retain unique contiguous ordering 1 to 25
+    assert gated["hiffi_xp_published_rank"].tolist() == list(range(1, 26))
+    # All records remain Tier 1
+    assert (gated["platform_evidence_tier"] == 1).all()
+    # Shortfall must be explicitly reported
+    assert audit["top_10_shortfall"] is True
+    assert audit["top_50_shortfall"] is True