The quiet corners of America
Quiet Corners scores rural U.S. counties on stability, remoteness, sprawl risk and
affordability, and surfaces the ones that are staying quiet and are likely to keep
staying quiet. The methodology below sets out how stability, remoteness and sprawl risk
are computed and how they roll up into the overall score, and the data trust model names
the source behind each input. The dashboard below is public and free to use in your
browser — no account, no signup.
Every data point comes from the U.S. Census Bureau or USDA, with one disclosed
exception: interstate proximity (30% of the sprawl-risk composite, below) is measured
against a hand-maintained waypoint list, not a government dataset. No commercial APIs,
no scraped listicles, no vibes.
Explore the map below, or filter counties directly by stability, remoteness, sprawl risk
or overall score.
Methodology
Independent scores, each 0-100:
Stability — Coefficient of variation (Bessel-corrected) plus linear regression slope
across 5 years of population estimates. Low CV + flat slope = high stability. Weighted
60/40 CV-to-slope.
Remoteness — Great-circle distance from county centroid to nearest city with
population over 25,000. Uses the full Census place gazetteer — capturing regional hubs,
college towns, and county seats that rural residents actually drive to. The pipeline
exports this as raw miles (distance_to_metro_mi), not a normalized 0-100 score; the
dashboard’s Remoteness filter slides across that raw distance, up to 250 miles,
and slides all the way down to Any, which switches it off: a county ten miles
from a small city can be as quiet as one ninety miles out, and a county whose
distance was never computed is not evidence that it is close to anything.
Sprawl Risk — A five-factor composite, all five live on this run: interstate
proximity (30%), building permit trend (25%), state migration acceleration (20%),
fast-growing metro proximity (15%), and recreation/retirement county typing (10%).
Lower is better. Permits and metro proximity used to be dead — the Census API retired
both endpoints — and are now read from the keyless bulk files on www2.census.gov
instead (Building Permits Survey county annual files; PEP subcounty estimates).
A county missing an input is scored over the factors it does have, with the remaining
weights renormalized, so a gap cannot quietly deflate a score toward “no sprawl risk”.
A factor that scores 0 from real data still counts at full weight.
The trust panel on the dashboard lists, per factor, how many counties it scored above
zero on the run that produced this page — read from the data, so it stays true across
regenerations. Those counts are not coverage rates. A factor reads 0 both when its
input is missing and when the county genuinely has no pressure from it: most rural
counties carry no USDA recreation or retirement type at all, migration scores 0 for
every state whose inward flow is flat or falling, and a county more than 100 miles from
an interstate scores 0 there by construction. Permits are the one factor where a low
count is partly a real gap — many rural counties have no usable multi-year permit
series in the survey’s county files.
Overall — Quietness 55% and Affordability 45%. Quietness is itself stability 40%,
remoteness 30%, and inverted sprawl risk 30%. Both levels renormalize over the inputs a
county actually has, and a county with nothing scoreable gets no score rather than a
zero. Livability was removed: it returned the affordability score verbatim, which
double-weighted affordability while advertising a dimension that did not exist.
Counties must have a USDA Rural-Urban Continuum Code of 6 or higher (nonmetro with urban
population under 20,000) to appear in results. Within qualifying counties, candidate
towns (incorporated places with population 1,000-3,000) are surfaced with scores
inherited from their parent county.
Reading the map
The county shading and the map key show one measure at a time, and the
Color the map by control chooses which: Stability, Overall, Quietness,
Affordability, or plain miles to the nearest city. The key relabels itself in
that measure’s own units — a distance key reads in miles, not on a 0–100 ramp —
and outlines and dot sizes follow the same bands, so the map is never colour
alone. It is separate from how the tables sort (Overall for counties, Stability
for candidate towns); changing the colour changes no filter and drops no row.
A county whose value was never computed is drawn in its own grey and listed as
Not measured, rather than shaded into the bottom band where a gap in the
data looked like a low result.
The map names two kinds of place. The towns it scores come from the candidate export, and they are small by definition — so the country-wide view also names the large places you would orient by, from a separate list of 347 cities that exists only to say where the small towns are. Those names are capped so they frame the map rather than fill it, and they carry the everyday form of the name rather than the Census one.
Each table says what it is ranked by, in words — Sorted by Overall, highest
first — and the heading it names carries a caret and an underline, not just a
colour. The county table and the candidate towns below it sort independently,
and neither follows the map’s colour. One line above the tables says all three
at once — Map color: Stability · County sort: Overall · Town sort: Stability —
because Stability is a component of Overall rather than a rival ranking of it, so
a county can shade dark on the map and still sit low in the table. It is written
from the live selection and follows every change you make to it.
The page sets figures and words in different faces on purpose. The score columns
stay monospace, because seven columns of digits only line up when every glyph is
the same width. Everything you read rather than compare — filter labels, column
headings, the map key, the sentences above the tables and the provenance line
under the title — is in the ordinary interface face, and the county’s own name is
the largest thing in its row.
On a phone each row becomes a card instead of a table line, and every measure comes
with it. The tables used to drop affordability, remoteness and sprawl below 1024px
while the filters that set them stayed — so the figure you had just filtered on was
the one off screen. Each value now carries the column heading beside it, read from
the table’s own header, so a card can never label a number with the wrong measure.
Data trust model
Every figure on this page is regenerated from source by a pipeline that refuses to
invent a number it does not have — but it discloses gaps two different ways depending
on the dimension. Stability, remoteness and affordability report a missing county’s
field as absent (null) rather than defaulted; the coverage panel states the real scored
percentage for each. The sprawl sub-factors instead report a per-factor non-zero count
in the sprawl-factors panel, and a factor with no input for a county is dropped from
that county’s composite with the remaining weights renormalized — never defaulted to a
convenient number. The generation timestamp is stamped into the exported data rather
than typed by hand.
Sources the pipeline draws on:
- County populations: Census PEP Vintage 2024 (2020-2024)
- County coordinates: Census Gazetteer 2024
- Nearest cities: Census Place Gazetteer 2024 (all places >25K)
- Rural classification: USDA Rural-Urban Continuum Codes 2023
- County typing: USDA County Typology Codes 2015 (recreation/retirement flags)
- Interstate proximity: Static, hand-maintained waypoint list along major US
interstates (422 points across 30 route chains, no duplicates), with distance measured
to the nearest route segment rather than the nearest point — not a government dataset
- County geometry: us-atlas
counties-10m.json (ISC License, © the us-atlas project) — a TopoJSON build derived
from Census TIGER/Line cartographic boundaries, served from this domain rather than a
third-party CDN - Building permits: Census Building Permits Survey, county annual bulk files
(
www2.census.gov/econ/bps/County/) — the API timeseries endpoint is retired; these
keyless files replace it - Fast-growing metro proximity: Census Subcounty Population Estimates bulk file
(SUB-EST2024) — the PEP place API endpoint is retired; this keyless file replaces it
- State migration: Census ACS 1-Year B07001 (Geographical Mobility)
- Affordability: Census ACS 5-Year (median home value, gross rent, household income)
- Candidate towns: Census Subcounty Population Estimates 2024 (SUB-EST2024)
No data is sampled, simulated, or interpolated beyond filling the 2001-2009 intercensal
gap with Census-published CSV data. What you see is what those sources reported.
The map, the geometry and every byte of data on this page are served from this domain.
There are no third-party scripts, no tile servers, and no analytics on it.