# SHARED_SCHEMA -- Five Dimensions (D1-D5) of the Parameterized Single-Schema Rubric

**Status:** Load-bearing. This is THE schema. Claim-type profiles re-weight it. Discipline priors modulate the weights. Neither replaces it.

**Provenance:** Phase 3 Tier-1 adjudication (2026-04-17) forced this from 5 parallel rubrics into 1 parameterized rubric. Literature basis: GRADE (per-outcome parameterization of a single schema), CERQual (same structure for qualitative), Petticrew & Roberts (one matrix, many cells). See S02_session_output.md.

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## The Five Dimensions

Every (source, claim) pair is scored against ALL FIVE dimensions. Dimensions are scored INDEPENDENTLY. No dimension is derived from another.

### D1 -- Inferential-Load Match

**Question:** Does the source carry the specific inferential load this claim's type requires?

**What "load" means per claim type** (full detail in CLAIM_TYPE_PROFILES.md):
- Descriptive -- provenance + authority + date (AACODS).
- Causal -- internal validity + identification strategy (RoB 2 / ROBINS-I / GRADE).
- Predictive -- out-of-sample calibration + track record (Brier / Good Judgment Project adaptation).
- Interpretive -- thickness + reflexivity + transferability (Hammersley / CERQual).
- Normative -- argumentative coherence + authorial accountability (Dorst / reflective equilibrium).

**Scoring (0-5 ordinal):** 0 = load absent or fabricated; 1 = load asserted but unsubstantiated; 2 = partial load present with gaps; 3 = load present and defensible; 4 = load well-substantiated; 5 = load demonstrably carried with explicit methodology.

### D2 -- Integrity Status

**Question:** What does the Source Integrity Screen (S2) report about this source's baseline integrity?

**Reads from S2:** retraction status, AI-contamination signal (with sparse-field caveat), publication-bias signal, citation-verification queue status.

**D2 does NOT re-run S2.** It reads the integrity_flags field and translates to 0-5.

**Scoring:** 5 = clean on all S2 axes; 3 = one minor flag (e.g., uncorroborated pre-print); 1 = serious flag (e.g., pub-bias suspected in weak-evidence field); 0 = confirmed retraction OR confirmed AI-fabrication OR unverifiable citation chain.

### D3 -- Lineage Independence

**Question:** Is this source independent from the other admitted sources for this claim, or does it inherit the claim from a common ancestor, co-author cluster, or citation cascade?

**Reads from R7.3 metrics** (LINEAGE_INDEPENDENCE.md):
- Bibliographic-coupling score (BC) vs other admitted sources for this claim.
- Amplification-vs-original-data classification (Greenberg 2009).
- Ancestor-overlap at depth 3.
- Community-modularity bucket (Leiden Q).

**Scoring:** 5 = genuinely independent (BC < 0.10, original data, distinct ancestor set); 3 = partial overlap (one shared ancestor, distinct authors); 1 = amplification-class with shared founder; 0 = citation cascade confirmed, no original contribution.

### D4 -- Admiralty Inputs

**Question:** What do the Admiralty A-F (reliability) and 1-6 (credibility) inputs say about this source, scored SEPARATELY?

**Hard rule:** A-F and 1-6 enter as TWO inputs. Do NOT average them into a single Admiralty score before D4 is written. The Baker 1968 A1/B2/C3 diagonal critique requires the two scales be visible and independently justified.

**Anti-collapse check:** If the reliability and credibility inputs track together (both high, both low) without independent evidence, emit `admiralty_collapse_suspected=true` into the D4 rationale. Document why the two scales moved together.

**Scoring of D4:** 5 = A1 or A2 with independently justified reliability AND credibility; 3 = B3 / C2 with clear justification; 1 = D-F or 4-6; 0 = F6 or missing inputs.

### D5 -- Discipline-Prior Alignment

**Question:** Does the source-property profile match what this claim's discipline privileges?

**Reads from DISCIPLINE_PRIORS.md.** Ethnography privileges thickness; econometrics privileges identification strategy; historiography privileges archival provenance; etc.

**Scoring:** 5 = profile matches discipline-privileged property set; 3 = partial match; 1 = profile mismatches (e.g., cross-sectional survey being used for causal-econometric claim); 0 = profile unsuitable for this discipline's inference standards.

---

## Output Schema for Step 2

For each (source, claim) pair, emit:

```
dimension_scores = [
  {dimension_id: "D1", score: <0-5>, evidence_excerpt: "...", rationale_one_line: "..."},
  {dimension_id: "D2", score: <0-5>, evidence_excerpt: "...", rationale_one_line: "..."},
  {dimension_id: "D3", score: <0-5>, evidence_excerpt: "...", rationale_one_line: "..."},
  {dimension_id: "D4", score: <0-5>, evidence_excerpt: "...", rationale_one_line: "...", admiralty_collapse_suspected: <bool>},
  {dimension_id: "D5", score: <0-5>, evidence_excerpt: "...", rationale_one_line: "..."}
]
```

All five entries MUST be present. Each rationale MUST be distinct and dimension-specific -- if two rationales are interchangeable, the schema has degenerated (ANTI_DEVIATION.md, CRAAP-reduction check).

## Non-negotiable rules

- Score the dimension you are on, not the composite. The composite is Step 4.
- If a dimension cannot be scored for lack of evidence, record `score=null` with the reason -- do NOT impute. Step 3 decides whether null on a load-bearing dimension triggers disqualifier.
- Per-dimension rationales survive into the final output (Step 7). The headline never erases them.
