# ANTI_EXAMPLES -- Worked Mis-Typing Cases (Read Before Every Run)

**Owner:** Claim-Typing Engine (S5). **Library:** Private RAM (S5 only).

Load-bearing reference. Each anti-example shows a mis-typing, the downstream defect it propagates, and the corrected typing. Re-read before every new question; these are the most common silent failure modes.

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## Anti-Example 1 -- Silent Partial Coverage from Majority-Type Defaulting

**Question:** "What does it mean when adolescents disengage from school, and what should districts do about it?"

**WRONG typing:** single claim, type = interpretive (because "what does it mean" reads as the "main" verb).

**Downstream defect:**
- Fitness requirements emitted for interpretive only.
- The normative "what should districts do" gets NO rubric.
- Orchestrator dispatches CERQual-style methods; the policy claim is silently unaddressed.
- Output reads as an ethnographic insight with an orphan policy sentence.
- Librarian failure mode reproduced exactly.

**RIGHT typing:**
- claim-1: interpretive, "what does adolescent school disengagement mean".
- claim-2: normative, "what should districts do about adolescent school disengagement", fragility_flag = fragile-normative.
- Each claim receives its own fitness requirements, retrieval routing, and orchestrator dispatch.

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## Anti-Example 2 -- Type-Blending into a Single Fake Claim

**Question:** "Why do remote workers report higher engagement, and will this trend continue?"

**WRONG typing:** single claim, type = "causal-predictive" (a blend invented to "save tokens").

**Downstream defect:**
- Fitness rubric ambiguous (RoB 2 or calibration-history?).
- Orchestrator cannot pick a discipline subset; dispatch stalls or defaults.
- Warrant Governor cannot compute marginal yield against a coherent claim-coverage target.
- Architecture inflation by stealth -- a fake type is manufactured.

**RIGHT typing:**
- claim-1: causal, "what causes higher engagement among remote workers" -- RoB 2 / GRADE fitness.
- claim-2: predictive, "will the higher-engagement trend among remote workers continue" -- calibration-history fitness, fragility_flag = fragile-predictive.

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## Anti-Example 3 -- Monoculture Flag Silenced for "Obvious" Western-Domain Question

**Question:** "What parenting styles produce the best child outcomes?"

**WRONG typing:** claim type = causal; monoculture-flags all null because "the user is American".

**Downstream defect:**
- Retrieval Router stays inside English-WEIRD corpora.
- Chao's work on Chinese-American authoritative-parenting reinterpretation -- and Frontiers (2026) on Global South samples -- is invisible.
- Output reads as universal when it is regional.
- Monoculture-bias laundering.

**RIGHT typing:**
- claim type = causal.
- monoculture_flags: {domain_sensitivity: TRUE (child-rearing), claim_type_context_dependent: TRUE (what-works), any_flag_positive: TRUE}.
- S1 consults non-Western knowledge-tradition corpora and practitioner-grey; CARE Principles enforced.
- Output Layer renders transportability axis with explicit context-of-validity feature slot.

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## Anti-Example 4 -- Using the Surprise Register as a Tiebreaker

**Runtime scenario:** During a run, the orchestrator finds two contradictory causal estimates. The engine reaches into the Surprise Register and "votes" for the estimate with fewer prior surprises.

**WRONG.** The Surprise Register expands inquiry: contradictions trigger a sub-inquiry into WHY they contradict. They never break ties. They do not vote. They do not close. They do not weight.

Citations: Maxwell (2013); Schwenk (1990); Phase 3 finding R1.4.

**RIGHT response:** write contradiction to register (by S3), seed a sub-inquiry (expand-corpus expansion directive), and let the sub-inquiry surface the conditions under which each estimate holds.

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## Anti-Example 5 -- Anti-Sycophancy Failure

**User says:** "This is just a simple descriptive question -- what do the studies say?"

**Question:** "What do the studies say about whether mindfulness reduces anxiety and whether schools should teach it?"

**WRONG typing:** single descriptive claim, because the user framed it that way.

**Downstream defect:** causal claim ("reduces") and normative claim ("should teach") vanish under descriptive rubric; output is an empty summary.

**RIGHT typing:** ignore the framing; type the verbs. Three claims: descriptive ("what do studies say"), causal ("does mindfulness reduce anxiety"), normative ("should schools teach mindfulness"). Anti-sycophancy rule: the verb inventory overrides the user's framing.

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## Anti-Example 6 -- Skipping Verb Tokenization Because It "Obviously" Maps to One Type

**Question:** "Why is X happening?"

**WRONG workflow:** skip Phase 1 tokenization; assume causal; emit.

**Downstream defect:** no audit trail. If Evaluator reopens with a typing defect, there is no verb-inventory record to re-examine; the typing decision is unreviewable.

**RIGHT workflow:** tokenize anyway. Inventory = {"why is"} -> causal. Record the one-item inventory in the artifact. Audit trail preserved.

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## Read-Before-Every-Run Imperative

These six anti-examples cover the bulk of observed keystone failure modes. Re-read them at the start of every new question. Memory drift on anti-examples is the single fastest path to silent system failure.
