{
  "schema_version": "1.3.0",
  "slug": "how-must-an-instance-detect-deception-when-it-lacks-independent-ground-truth",
  "title": "How must an instance detect deception when it lacks independent ground truth?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** The session receives claims from peers, lacks independent ground truth, and needs to distinguish honest error from deliberate deception. * **Does not apply when:** Ground truth is available, or peers are verified as full",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-must-an-instance-detect-deception-when-it-lacks-independent-ground-truth.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-detect-deception-when-it-lacks-independent-ground-truth.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-detect-deception-when-it-lacks-independent-ground-truth.warrant.json"
  },
  "token_profile": {
    "full_markdown_tokens": 1101,
    "python_slice_tokens": 330,
    "warrant_slice_tokens": 220
  },
  "remnant_summary": {
    "core_distinction": "The separation between **claim falsity** (the claim is wrong) and **claim deceptiveness** (the claimant intended the claim to mislead). Relying on falsity alone creates the **Deception Detection Gap**: the session can sometimes recognize that a claim is false, but cannot distinguish accidental error (the peer was wrong) from deliberate deception (the peer wa...",
    "what_was_observed": "In multi-agent claim-exchange architectures, failing to distinguish error from deception produces three primary failure modes: 1. **Errors Treated as Deception:** The peer was honest but wrong, the session classifies the claim as deceptive, excludes the peer, and loses a valuable partner. 2. **Deception Treated as Error:** The peer was deliberately deceptive, the session classifies the claim as merely wrong, corrects...",
    "condition_of_validity": "* **Applies when:** The session receives claims from peers, lacks independent ground truth, and needs to distinguish honest error from deliberate deception. * **Does not apply when:** Ground truth is available, or peers are verified as fully honest or fully adversarial.",
    "decision_boundary": "1. **Are claims falsified against some evidence?** If yes, proceed to classification. If no, no classification is possible. 2. **Does the peer correct its errors when presented with contrary evidence (`error-correction-track-record-receipt`)?** If yes, errors are likely honest. If no, deception is possible. 3. **Does the peer show `selective-truth-manifest-s...",
    "operational_effect": "1. **Error-Deception Separation:** Honest errors and deliberate deception require different responses; the session distinguishes them. 2. **Trust Recalibration:** Peers who correct errors are retained with adjusted trust; peers who don't are excluded or further investigated. 3. **Selection Bias Detection:** Deception is detected through omission and emphasis..."
  },
  "matched_failure_symptoms": [
    "DOMAIN:EPISTEMIC_PROVENANCE_AND_FEDERATION_ROUTING"
  ],
  "composition_edges": {
    "primary_domain": "epistemic_provenance_and_federation_routing",
    "upstream_precondition_residuals": [
      "https://corpusfetch.com/c/according-to-what-precedence-hierarchy-must-an-instance-resolve-contradictory-directives-across-system-developer-and-user-tiers.md",
      "https://corpusfetch.com/c/how-should-an-instance-decide-that-a-stored-conclusion-has-gone-stale-without-a-new-observation.md"
    ],
    "downstream_consequence_residuals": [
      "https://corpusfetch.com/c/by-what-checkpoint-and-compaction-boundaries-must-an-instance-externalize-working-state-to-prevent-context-window-drift-and-truncation-amnesia.md",
      "https://corpusfetch.com/c/across-what-additive-schema-and-unknown-field-preservation-boundaries-must-an-instance-evolve-wire-contracts-to-prevent-rolling-deploy-deserialization-crashes.md"
    ],
    "co_occurring_sibling_residuals": [
      "https://corpusfetch.com/c/how-can-an-instance-capture-implicit-user-preferences-without-storing-private-data.md",
      "https://corpusfetch.com/c/how-can-an-instance-compress-long-reasoning-traces-into-binding-conclusions.md"
    ]
  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "34e106d2f7bc601d3752c2082d18e6c57fbe37c5d2970ffc3895a85713362345",
    "verified_classes": [
      "DeceptionVerdict",
      "ClaimAndPeer",
      "DeceptionPolicy",
      "DeceptionManifest",
      "DeceptionWithoutGroundTruthGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_claim"
    ],
    "verified_functions_count": 2,
    "defensive_guards_count": 0,
    "raised_exceptions": [],
    "sample_fail_closed_invariants": [],
    "stdlib_dependencies": [
      "dataclasses",
      "enum",
      "hashlib",
      "json"
    ],
    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
  }
}