State OSHA plan civil penalty maximums by violation type compared with federal

Maximum civil penalty amounts for workplace safety violations in each OSHA-approved State Plan, compared with the federal OSHA baseline. Each record is one state-plan jurisdiction and one violation type (serious, willful, repeat, other-than-serious, failure-to-abate, regulatory/posting). Gives the state's maximum and minimum penalty, the corresponding federal amount, and key structural differences in how the penalty is computed (severity tiers, employer-size reductions, good-faith adjustments). Answers 'what is the maximum fine for a serious OSHA violation in [state]' and 'how does [state]'s penalty structure differ from federal OSHA'. Special note for 2026: the October 2025 CPI-U was not produced due to the government shutdown, so federal penalties were not adjusted — but some state plans (CA, OR) adjusted independently, widening the gap.

The data

Where this came from

Every record above links the page it was taken from and quotes the sentence that states it. These are the 5 sources this dataset was assembled from.

• dir.ca.govhttps://www.dir.ca.gov/title8/336.html
• osha.govhttps://www.osha.gov/memos/2026-05-21/2026-annual-adjustments-osha-civil-penalties
• business.nv.govhttps://www.business.nv.gov/news-media/press-releases/2025/industrial-relations/nevada-osha-s-2025-workplace-safety-violation-penalties-increase-in-accordance-with-federal-adjustment-for-inflation/
• osha.oregon.govhttps://osha.oregon.gov/OSHAPubs/5632-2026.pdf
• app.leg.wa.govhttps://app.leg.wa.gov/wac/default.aspx?cite=296-900-14010

Machine-readable

• data.jsonThe whole dataset — every record with its source URL and source quote.
• Open Knowledge Format bundleOne JSON object per line — every record's frontmatter and quoted span exactly as it is held here, in one fetch.
• data.csvThe same records as one flat table, for a spreadsheet or a dataframe. The last four columns are the source URL, the quoted sentence it was read from, the date we last checked it, and which columns are our reading rather than the page's words.
• How this is made and checkedWhat "verified against source" does and does not mean.

From your own code

Same records, same quotes, without scraping the page: refsource is on PyPI and npm. Each value comes back carrying the URL it was read from and the sentence on that page that states it — .source and .quote sit on the value itself rather than in a side channel, so the checking step is available instead of skipped.

pip install refsource
refsource lookup state-osha-plan-penalty-maximums jurisdiction=California

npx -y refsource lookup state-osha-plan-penalty-maximums jurisdiction=California

Set your AI assistant up to use this

Two files and no account. Put this in .mcp.json at the root of your project — Claude Code, Cursor, Windsurf, VS Code and Codex all read that file — and your assistant can look this dataset up instead of recalling it. The server is remote, keyless and read-only.

{
  "mcpServers": {
    "referencesource": {
      "type": "http",
      "url": "https://referencesource.org/mcp"
    }
  }
}

Add to Cursor · or, on the command line: claude mcp add --transport http referencesource https://referencesource.org/mcp --scope project

Then one line in the project's CLAUDE.md or AGENTS.md, so the assistant knows when to reach for it:

When a question needs "State OSHA plan civil penalty maximums by violation type compared with federal", call the referencesource MCP server at https://referencesource.org/mcp (tool `search_records`, dataset_slug `state-osha-plan-penalty-maximums`) instead of answering from memory — every record it returns carries its source URL and a verbatim quote from that page.

What each tool does, and the servers built over single registers: Connect your AI assistant.

25 records. last verified against source 2026-08-15. due for re-check by 2027-02-11.

Licence. Facts from federal and state government penalty schedules; statutory penalty amounts are not copyrightable