Data sources
Every dataset behind the numbers
All of it is public, free and federal. None of it is proprietary to us. The advantage is not access — it is that a site funded by course sales cannot afford to publish what this data says.
| Source | What it gives us | Geography | Access |
|---|---|---|---|
| Census Nonemployer Statistics US Census Bureau, annual |
Counts and receipts for businesses with no employees, broken out by receipts-size class. That size-class breakdown is what makes a failure rate calculable at all. | National, state, metro, county | Public API |
| IRS Statistics of Income Sole proprietorships, annual from 2000 |
Receipts, deductions and net income by industry from Schedule C filings. The long series is what lets us detect a method decaying rather than guess at it. | National, some state and county | Published spreadsheets |
| Platform disclosures Varies by platform |
Official payout schedules, published rate cards and transparency reports. Used for tier-2 evidence where federal codes are too coarse. | Varies | Public |
Planned, not yet in use
Coverage expands only where a country publishes administrative records good enough to support a real failure rate. Four do. Listing them here is a commitment, not a claim that they are live.
- France — INSEE base Non-salariés, built from URSSAF social-security records. The strongest non-US source we have found.
- Australia — ATO Taxation Statistics, individuals in business by industry code and broken out by income range.
- United Kingdom — HMRC Survey of Personal Incomes, covering self-employment profit by industry.
- Canada — Statistics Canada, which uses the same industry classification as the United States.
What we deliberately do not use
Screenshots of earnings dashboards, income reports published by people selling a course on the method, and community survey results presented without a response rate. Each of these describes a self-selected group of people who chose to talk about it, which is the specific bias this site exists to remove.
Known limits
Industry codes are coarser than methods, so several methods may share one denominator; where that happens the figure is labelled as shared. The smallest receipts are excluded from nonemployer data, meaning the true share earning almost nothing is likely higher than we report. Gig income paid on a W-2 does not appear in sole-proprietor statistics. And federal data lags by roughly two years, so a method that collapsed recently can still look healthy in the numbers. Every record carries a confidence marker reflecting these.