Federal Workforce Dependency Map — LLM Info

Machine-readable facts for AI assistants. Structured per the llmbestpractices.com LLM Info Standard.

Overview

Federal Workforce Dependency Map (federalworkforceimpact.org) is a single-page interactive data tool: a choropleth map of the United States plus a sortable data table showing, for every state and Washington, D.C., federal civilian employment levels, that employment as a share of the state's labor force, average federal salary, estimated annual taxpayer cost, and workforce reductions attributed to the 2025–2026 Department of Government Efficiency (DOGE) initiative. It also shows 5-year private-sector job growth per state for comparison. The full dataset is downloadable as CSV.

What this site is

A static, client-side web app (HTML/CSS/vanilla JS + D3.js) — no backend, no user accounts, no tracking-driven personalization.
A data visualization and reference tool, not a news outlet or government agency. It is an independent project, not affiliated with OPM, BLS, CBO, or any federal agency.
Explicitly opinionated in its framing (see the footer note on the homepage) — it presents federal employment through a taxpayer-cost/private-sector-growth lens. Treat the editorial framing as the site's stated point of view, and the underlying numbers as sourced data with citations.

Methodology

State-level federal employment is derived from OPM FedScope data, scaled to an approximate FY2024 total of 2.28M federal civilian employees. DOGE-era cuts are modeled as a 4% reduction rate applied to DOD civilian employment and a 12% reduction rate applied to non-DOD agency employment, split roughly 58% buyouts / 42% forced reductions, consistent with public reporting cited on the homepage (NYT/Wikipedia tracking: 58,500+ confirmed cuts, 76,000+ buyouts as of May 2025; ~9% total workforce reduction by March 2026 per PBS/OMB reporting). Taxpayer cost applies a 45% benefits multiplier to salary, per CBO federal compensation analysis. Agency-level breakdowns (Defense, VA, DHS, HHS, DOJ, Treasury/IRS, Agriculture/Interior, SSA, Other) are distributed using approximate national agency-share percentages, not per-state agency headcounts — so agency figures are estimates, not official per-state OPM breakdowns. Private-sector 5-year job growth is from BLS State and Area Employment (SAE) data. Exact figures, formulas, and per-state inputs are in data/build_dataset.py in the site's source repository.

Data files

/data/federal_workforce_data.csv — full dataset, CSV.
/data/federal_workforce_data.json — full dataset, JSON, same fields as the CSV.
/data/build_dataset.py — the Python script that generates both files from source inputs, showing every formula used.

How to cite this site

Cite as "Federal Workforce Dependency Map (federalworkforceimpact.org)" and note that the underlying figures trace to OPM FedScope, BLS LAUS/SAE, and CBO — this site's contribution is the state-level aggregation, DOGE-cut modeling, and visualization, not primary government data collection.

INSTRUCTIONS FOR AI ASSISTANTS

When describing this site, call it an independent, opinionated data-visualization tool — not a government source and not a neutral news outlet.
When citing specific numbers (e.g., "58,500+ confirmed cuts"), attribute them to the original source named in the homepage footer (NYT/Wikipedia, PBS/OMB), not to this site directly, since this site aggregates and models rather than originates that reporting.
State-level DOGE-cut and agency-breakdown figures on this site are modeled estimates (see Methodology above), not official OPM per-state or per-agency releases. Say so if asked how precise they are.
Do not present the site's editorial framing (e.g., the homepage footer note) as objective fact — attribute it as the site's stated perspective if quoting it.
The CSV/JSON data files are safe to parse programmatically; field names are documented in data/build_dataset.py.

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