How we know this
Sources & Methodology
The point
Most political data is built to win an argument. This is built to survive one. Every metric uses the same formula for every president — if a number makes someone look good, we show it; if it makes someone look bad, we show that too. The test for every page: would it survive scrutiny from someone who disagrees with the person who built it?
The non-negotiable principles
- No bias. Same formula, every president, both parties.
- Lead with the question people ask, not the metric academics measure.
- Green/red means good/bad for workers — never party colors.
- Context is mandatory. What each president inherited, what hit them, and what they did.
- Prove it or flag it. Measured outcome, correlation, or opinion — we label which.
- Plain English. If it needs a degree to understand, it's not done.
What we can prove vs. what we suspect
The whole project lives or dies on this line. When the data proves something, we say it plainly. When it's a strong correlation but not proven cause, we say that. When it's opinion, it doesn't go in. Approval ratings and historian rankings measure perception, not fact; unemployment and inflation are measured outcomes. We tell you which kind of claim each number is.
Sources by topic
Every dashboard names its source on the chart and links back here. Grouped by the question each one powers:
Money, cost of living & who's getting ahead
Affordability dashboard- U.S. Census Bureau — income, poverty, health-insurance coverage (incl. the American Community Survey)
- Bureau of Labor Statistics — inflation (CPI) and wages
- Congressional Budget Office & U.S. Treasury — national debt and tax distribution
- Federal Reserve — household wealth (Survey of Consumer Finances) and homeownership
- FRED (St. Louis Fed) — real median household income series
Jobs & work
Affordability dashboard- Bureau of Labor Statistics — employment, unemployment rate, labor-force participation
Health & life expectancy
Everyday Life · Health (in progress)- CDC / National Center for Health Statistics — life expectancy and health outcomes
- U.S. Census Bureau — health-insurance coverage
Approval & character traits
Stability dashboard- Gallup — presidential job approval (1981–present) and personal-character traits (1996–present)
- Reuters/Ipsos, YouGov, AP-NORC, Quinnipiac — approval polling, Trump II
Promise-keeping
Stability dashboard- PolitiFact — Obameter / Trump-O-Meter / Biden Promise Tracker (Obama onward)
Historian rankings
Stability dashboard · Presidents- C-SPAN Historians Survey of Presidential Leadership (presidents ranked after they leave office)
Economic mobility
Everyday Life · Mobility (in progress)- Opportunity Insights (Raj Chetty et al.) — intergenerational mobility
International comparisons
The World (in progress)- OECD, World Bank, ILO — pay, healthcare, life expectancy, and mobility vs. peer nations
Polarization & common ground
Common Ground (in progress)- Pew Research — polarization and bipartisan-support polling
Data centers & electricity costs
Data Centers feature- Gallup (Mar 2–18 2026, n=1,000) — opposition to local data centers, by party and region
- Pew Research (Jan 20–26 2026, n=8,512) — perceived impacts on energy costs, environment, jobs
- CBS News / YouGov (June 2026) — opposition and energy-bill concern
- IEEFA & PJM Base Residual Auctions — wholesale capacity prices ($28.92 → $269.92 → cap)
- Monitoring Analytics — PJM's independent market monitor — 63% of the increase / ~$9.3B from data centers
- Rutgers / Bloustein (NJ State Policy Lab, June 2026) — realized ZIP- and utility-level bill effect
- Brookings (May 2026, ~770 facilities) — employment effects and mistargeted incentives
- Bloomberg Tax / NY Focus, CSG South / Virginia JLARC, LaborWise — tax breaks and jobs-per-facility
- Lawrence Berkeley National Laboratory — residential electricity price trends; CUB — capacity-market reform
- EESI (orientation, secondary); NRDC (~$70/mo-by-2028 projection — flagged as a projection)
Why this exists
The person building this is openly biased left — and built the project specifically to counteract that. The guardrails above aren't decoration; they're the reason it exists. Where a source leans (for example, historian surveys skewing left because academia self-selects, not because smarter people are liberal), we say so on the page rather than hide it.