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metadata
pretty_name: >-
  WARN Act notice-type codes crosswalk - every raw state string and what it
  means
license: cc-by-4.0
language:
  - en
task_categories:
  - tabular-classification
  - text-classification
tags:
  - warn-act
  - data-cleaning
  - entity-resolution
  - normalization
  - crosswalk
  - codebook
  - data-dictionary
  - layoffs
  - layoff-notices
  - plant-closings
  - labor
  - labor-market
  - public-records
  - government-data
  - daily-updated
  - united-states
size_categories:
  - n<1K
configs:
  - config_name: crosswalk
    data_files: data/notice_type_crosswalk.csv

WARN Act notice-type codes — the crosswalk

Every US state publishes WARN Act layoff notices with a free-text column saying what kind of event it is. The statute recognises two: a plant closing and a mass layoff. Across 48 states that column contains 491 distinct exact strings (474 once you fold case).

This dataset is the crosswalk: one row per raw string, how many notices carry it, which states emit it, and what it normalizes to.

The finding that matters

460 of the 491 strings (94%) are used by exactly one state. Only 31 are shared across states at all.

There is no common vocabulary. CL means closure in Indiana and Wisconsin; Illinois fills the column with State; five states write WARN — the name of the statute — where the event type belongs. 324 strings appear on a single notice in the entire archive.

This is why "just parse the state files" does not converge: there is nothing to parse toward until someone reads all 48 vocabularies and keeps reading them as states change their exports.

Vocabulary by what it maps to

maps to distinct strings
layoff 161
closure 115
mixed (both terms present) 18
unknown (deliberately unmapped) 197

unknown is a real category, not a failure to try. It covers blanks, strings that name which statute applies rather than what happened (State, WARN, numeric record codes), and strings that name a cause (loss of contract, sale of company, COVID-19) rather than an event. Guessing these would manufacture thousands of false rows that no downstream user could detect.

The 12 most common strings

raw value maps to notices states used by
(blank) unknown 13,209 29 AK CO CT DC FL HI ID KY LA MA MN MO MT ND…
Layoff Permanent layoff 7,812 2 CA TN
Closure closure 6,067 15 AK AL CO KY MI MS NC NE NV NY OH PA VA WA WV
Layoff layoff 5,939 15 AK AL KY MI MO MS NC NE NV NY OH PA VA WA WV
State unknown 4,845 1 IL
Closure Permanent closure 4,164 2 CA TN
Layoff Temporary layoff 3,657 2 CA TN
WARN unknown 1,658 5 AZ DE KS ME VT
Closing closure 1,196 8 CO CT IA MN MO PA RI WV
Plant Closing closure 917 3 MI OK PA
CL closure 862 2 IN WI
Mass Layoff layoff 837 7 CO IA MD MI OK PA WV

Files

  • data/notice_type_crosswalk.csv — 491 rows: raw_value, kind, permanence, reason, notices, n_states, states.

Covers all 59,806 notices in the archive as of 2026-09-12; rebuilt daily in the same pipeline run as the notices themselves, so the two can never disagree.

Limits — read before citing

  • These are notices, not verified job losses. A WARN notice can be amended, rescinded, or never carried out.
  • The mapping is conservative: anything that does not clearly say closing or layoff is left unknown rather than guessed.
  • permanence is only populated where the state says so; most states do not.
  • Counts are of notices, not workers.

Related

License CC-BY-4.0. Built from public state government records.

Use it, or keep watching it

This dataset is one cut of a single daily rebuild: 61,306 US WARN Act layoff notices from 48 state agencies, 1988 to today, one schema, no login, no delay, CC BY 4.0. Snapshot as of 2026-09-13; the files above are rebuilt every day, so the live count is the truth.

Look something up right now — free, no signup, nothing to install. Check any employer or state against the last 180 days → It runs in your browser against these same files.

Building something with it? The same files are a free HTTP API — JSON and CSV, no key, no signup, access-control-allow-origin: * so fetch() works from a browser: endpoints, schema and curl examples →

Or have it watch a list for you. Coming back to look is the part a CSV cannot do. WARN Watch — $49 for a year, one payment, nothing auto-renews, 14-day refund, no login: up to 500 employer names plus whole states, matched on every daily refresh, delivered to a private alert page + calendar (.ics) + RSS + an optional Slack / Discord / Teams webhook. Every alert carries that employer's whole filing history from the archive, which a keyword rule on an RSS feed cannot see. There is no built-in email — we do not claim one.

Reaching a human. WARN Feed is published by APProjects, an automated data publisher — that is stated plainly rather than dressed up. Corrections, coverage gaps, schema questions and refund requests all go here and are read: open an issue. Payments are handled by Gumroad as merchant of record, so an invoice can carry your company name.

Source, scrapers and methodology · the 48-state site