About ctzn.pub
A publishing platform that cannot make up a number.
ctzn.pub computes statistics from rigorous public surveys and administrative data — GSS, ANES, CES, CDC, Census, and more — publishes them as interactive essays, and ships the same computations as machine-readable claims. Every figure survey-weighted. Every claim sourced.
From raw data to a published claim
Four stages, the same for every article on the site.
Public sources
Public survey and administrative microdata — GSS, ANES, CES, YRBS, MTF, SCF, CDC PLACES, Census/ACS and more — pulled from the canonical source and pinned to a versioned extract, not a live query.
Design-correct computation
Estimates computed the way the survey’s own methodology demands: the right weights, replicate variance, small-cell suppression — applied, not approximated.
Interactive essays
Computed figures become interactive charts and maps, woven into long-form essays that explain what the data shows and why it matters. Source cited on every figure.
Machine-readable surfaces
Published articles ship as clean Markdown mirrors, a claims feed, and structured data an AI engine can cite. A full claims API and MCP server are in development.
Peer review, built into the machine
Before anything is computed at scale from a new source, we write down the full analysis plan — which estimates get precomputed, under which survey weights, with which demographic cuts, and what gets suppressed — and render it into a single readable document. A human statistician reviews the statistics in that plan: the survey-design handling, the cuts, the cell-size rules, the exact wording of what we'd claim.
The review is binding, not a courtesy read. The approval is tied to a fingerprint of the exact plan a reviewer read — edit the plan afterward, and the fingerprint breaks, reopening review. Small cells are pooled and the pooled range is labeled; we never lower a suppression floor to make a cut work. Series breaks — a survey redesign, a mode change, a weight splice — are shown as breaks, never drawn through as one continuous line.
One design mistake would replicate across thousands of published numbers. So a person signs every plan before a single number is computed.
There is deliberately a human at the other end of every one of these.
What we won't compromise on
Four standing rules, not marketing.
- Academically rigorous
- Every figure is survey-weighted and every claim traces back to its exact source — no vibes, no invented numbers.
- Pinned to a snapshot
- Every figure is pinned to a versioned data extract, not a live query that can drift under you. We refresh the pin when a source publishes a new wave, and every article states its vintage.
- Agent-ready surfaces
- Markdown mirrors, a machine-readable claims feed, and JSON-LD — the surfaces AI engines cite today.
- Built to read
- Interactive charts and maps designed for long-form reading — built for researchers and journalists first, machine-readable second.
Who runs this
ctzn.pub is built and run by a small team working directly with the survey methodology — the same people who compute the figures, write the essays, and review every published number.
Contact
Questions about a figure, a correction, a licensing question, or interested in the institutional library — reach us directly.
info@ctzn.pubMachine surfaces
What machines can read today: Markdown mirrors of every published article, a machine-readable claims feed, and structured data on every article page. No key required — these are public, crawlable surfaces.
Markdown mirrors
Every published article is also served as clean, extraction-friendly Markdown — prose intact, each chart replaced by its sourced takeaway.
GET /api/md/<username>/<slug>Claims feed
A machine-readable feed of sourced findings from published articles — the numbers, their source surveys, and the article they came from.
GET /claims.jsonStructured data
Published articles carry Schema.org JSON-LD (Article + Dataset), so search and answer engines can attribute every figure.
application/ld+json on article pagesOpen to AI crawlers
robots.txt explicitly welcomes GPTBot, ClaudeBot, PerplexityBot and peers across all public content.
GET /robots.txt{
"generated": "2026-07-03T22:14:36.012Z",
"count": 2,
"claims": [
{
"article": "The widening mental health gap among US teens",
"url": "https://uma.ctzn.pub/the-widening-mental-health-gap-among-us-teens-wyl28",
"title": "Poor Mental Health Among US High School Students",
"source": "YRBS",
"takeaway": "Female: 40.8 (2021) → 38.8 (2023), -2.0; Male: 18.1 (2021) → 18.8 (2023), +0.8."
}
]
}On the roadmap
A full public REST API and MCP server over the article and claims catalog is in development and not yet available. Nothing on this page requires a key or a plan — when a metered API ships, it will be documented here first.