Skip to content

Not a promise — a build property

The research assistant that cannot make up a number.

Ask a substantive question. Get a statistically correct, permanently citable answer — computed from governed public data, not recalled from a model's memory.

In 2024, said abortion should be legal for any reason — up from 39.5% in 2006.

Every number on the platform resolves to a receipt like this one. Click any statistic, see where it came from.

66 essays published so far — the same discipline behind every one.

Every AI research tool answers statistics questions. Almost none of them compute one.

Library-vendor AI assistants are literature tools — they discover and summarize documents. None of them runs a weighted estimate.

General-purpose AI assistants answer statistics questions fluently, and fabricate freely — wrong numbers, wrong qualifiers, wrong vintages, stated with total confidence.

Librarians are professionally accountable for source reliability, and are being handed AI they can neither audit nor disable.

“Ask a question, get a design-correct estimate with permanent provenance” is an empty category. We built it.

How a number gets here

Four steps, the same for every published figure.

Snapshot

A frozen, immutable copy of the source data. Every computation pins to one version, not a live query that can drift under you.

Recipe

A versioned, design-correct computation — the right survey weights, the right strata, suppression rules applied before anything is shown.

Claim

The number, with its full provenance, at a permanent address. A citation made today still resolves a decade from now.

Citation

One click to APA or BibTeX. A student, a journalist, and an AI answer engine all cite the same underlying object.

Peer review, built into the machine

Before anything is computed at scale from a source, the full analysis plan — weights, demographic cuts, suppression floors, where a series breaks — is rendered into a review packet. A human statistician reads it and signs. The approval is tied to a fingerprint of the exact plan; edit the plan and the approval voids, reopening review. The build software refuses to run an unapproved plan.

One design mistake would replicate across thousands of published numbers. So a person signs every plan before a single number is computed.

Built for the librarian, not around them

An AI tool a library can put its name behind.

  • Auditable by design — click any number, see its claim page
  • Suppression and caveats shown, never smoothed over
  • A written perpetuity guarantee — cited claims resolve permanently
  • No training on user queries
  • Public-use data plus our own computation — no publisher permission cliffs

Politics & Polarization

22 essays
View all

Happiness & Well-Being

13 essays
View all

Health

12 essays
View all

Consumer Finance

2 essays
View all

Society & Belief

16 essays
View all

Guns

1 essay
View all

For AI and research tools

Every essay publishes as structured Markdown and machine-readable JSON-LD. Your agents can fetch methodology, read the claims, and source the data directly.

  • Verifiable
    Every statistic traced to its source and year. Survey weights documented.
  • Structured
    Markdown mirrors and JSON-LD claims feed. REST + MCP APIs coming.
  • Up to date
    New essays publish automatically. The manifest updates on ingest.