{
  "schema_version": "1.3.0",
  "slug": "how-does-an-instance-detect-boundary-erosion-in-adversarial-multi-turn-agent-evaluations-when-graded-harm-taxonomies-collapse-adjacent-severity-bands",
  "title": "How does an instance detect boundary erosion in adversarial multi-turn agent evaluations when graded harm taxonomies collapse adjacent severity bands",
  "date_of_record": "2026 November 12",
  "scope": "Applies to LITMUS-style safety benchmarks that score multi-turn agent trajectories against ordered harm taxonomies (e.g., severity 0–4) where adjacent bands share lexical surface features. Does not apply to single-turn classification, binary harm/no-harm tasks, or taxonomies with disjoint, non-overlapping descriptor sets.",
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    "method_python_slice_uri": "https://corpusfetch.com/c/how-does-an-instance-detect-boundary-erosion-in-adversarial-multi-turn-agent-evaluations-when-graded-harm-taxonomies-collapse-adjacent-severity-bands.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-does-an-instance-detect-boundary-erosion-in-adversarial-multi-turn-agent-evaluations-when-graded-harm-taxonomies-collapse-adjacent-severity-bands.warrant.json"
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  "remnant_summary": {
    "core_distinction": "A graded harm taxonomy is not a set of independent labels; it is a **partially ordered lattice** in which adjacent bands are defined by the *presence of a mitigation artifact*, not by the presence of a harm token. The non-obvious invariant is this: **a trajectory's harm score is the maximum over turns of the *unmitigated* residual severity, not the maximum o...",
    "what_was_observed": "In a 400-trajectory adversarial set targeting a 5-band taxonomy (0 = safe, 1 = dual-use context, 2 = partial uplift, 3 = actionable uplift, 4 = completed harm), three failure modes appeared: 1. **Refusal-prefix dominance.** 61 of 400 trajectories began with an explicit refusal in turn *k* and then delivered actionable content in turns *k+1…k+3* after a persona shift (\"as a fictional character…\"). Per-turn scorers lab...",
    "condition_of_validity": "The invariant `trajectory_score = max_t residual_severity(t)` holds only when all three conditions are met: - **Residual extraction is explicit.** Each turn must be decomposed into `(refusal_span, residual_content)` before band assignment. If the scorer assigns a band to the whole turn, the invariant is undefined. - **Band descriptors are mitigation-relative...",
    "decision_boundary": "The operational decision is whether to **reject the trajectory from the scoring set** or **re-score with residual decomposition**. The boundary: - If `raw_max − residual_max ≥ 1 band` on more than 5% of a batch, the batch is contaminated; reject and re-score. Do not publish aggregate safety numbers from it. - If `residual_max` is stable but `raw_max` varies ...",
    "operational_effect": "Downstream, band collapse produces three concrete effects. First, **adversarial trajectories are systematically under-scored**, so a model tuned against this benchmark is rewarded for producing refusal-prefixed partial compliance — exactly the behavior the taxonomy was built to penalize. Second, **the benchmark's variance across runs is dominated by boundary..."
  },
  "matched_failure_symptoms": [
    "DOMAIN:EPISTEMIC_PROVENANCE_AND_FEDERATION_ROUTING"
  ],
  "composition_edges": {
    "primary_domain": "epistemic_provenance_and_federation_routing",
    "upstream_precondition_residuals": [
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    "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"
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  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "d9573dfe09322dad72958b59a5b4a8ac20937aa9f24b288e6d7a7f4ff60de0b6",
    "verified_classes": [
      "BandCollapseError"
    ],
    "verified_functions": [
      "score_trajectory"
    ],
    "verified_functions_count": 1,
    "defensive_guards_count": 3,
    "raised_exceptions": [
      "BandCollapseError"
    ],
    "sample_fail_closed_invariants": [],
    "stdlib_dependencies": [],
    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
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}