Methodology

Every page on Typical Female is built on primary sources. This page explains our sourcing hierarchy, verdict categories, and review process — so you can read our work with a clear view of what we've done and what we haven't.

Sourcing hierarchy

For any data point we publish, we try to use sources in this priority order:

1. Government statistical agencies — BLS, Census, NHTSA, FBI UCR, CDC, NIH, NSF, Department of Education. These are our default when any relevant dataset exists.
2. Peer-reviewed research — prioritizing meta-analyses and large-N replications over single studies. When citing a single study, we note the sample size, method, and year.
3. Institutional research centers — Pew Research, Catalyst, CAWP (Rutgers), McKinsey, AAMC, ABA, RAND, and other established non-governmental data sources.
4. Industry sources — Bloomberg, Nielsen, Fidelity, equity research — used only when governmental or academic sources don't cover the topic.
5. Primary documents — original papers, laws, charters, transcripts, when quoting positions or historical events.

Verdict categories on Atlas entries

Every Stereotype Atlas entry carries one of six verdicts, based on the consensus of the cited data:

• Debunked — The data directly contradicts the stereotype. The stereotype is materially false.
• Mostly myth — Small grain of truth, but the popular version significantly overstates or misframes it.
• Mixed — Evidence points both ways; the claim depends heavily on context, measurement, or subgroup.
• Partially supported — Some aspects are supported; others aren't. The stereotype captures part of the picture.
• Supported with context — The stereotype reflects a real average difference, though the cultural interpretation often runs beyond what the data supports.
• Insufficient data — We cannot currently find enough rigorous data to assign a verdict.

What we won't do

• Use a citation we can't verify. If a frequently-quoted statistic has no traceable source, we exclude it even when it supports the story we're telling.
• Assign a verdict more definitive than the evidence. 'Debunked' is reserved for stereotypes where the data directly contradicts the claim — not for stereotypes we disagree with.
• Paraphrase a study to say something it doesn't. Our methodology is to quote the finding as close to the original wording as possible and link to the primary source.
• Publish without sources. Every page on this site that makes a factual claim has a linked source.

State-level data

State pages use one source: the Census Bureau's American Community Survey (ACS) 2024 1-year estimates, table B20017, median earnings of women and men who worked full-time, year-round. We show each median with its margin of error (90% confidence) and the women-to-men ratio. Because each state figure has a margin of error, small differences in rank between states are not meaningful.

We no longer publish state legislature counts or state "firsts" on these pages. For current representation numbers, see the Center for American Women and Politics (CAWP) at Rutgers.

Profession × state estimates

The Pay Gap Lookup shows national median weekly earnings by occupation from BLS (CPS Table 39, 2025 annual averages). When you also pick a state, it shows a modeled estimate, not a measured figure: the national BLS median for women in that occupation multiplied by the state's ACS women-to-men ratio and divided by the national ACS ratio (0.831). This assumes an occupation's pay gap in a state tracks the state's overall gap, which is often not true. Read it as a rough comparison only.

Review

Pages are reviewed on publication and again at the 'Last reviewed' date shown at the bottom of each page. We re-verify sources, update statistics when new data is released, and correct errors. If you spot one, email hello@typicalfemale.com — we correct transparently and note significant changes in the page's update log.

Tools methodology

Each interactive tool (Pay Gap Lookup, Emotional Labor Estimator, Stereotype Fact-Check) has a detailed methodology section on its own page. Calculations are client-side, deterministic, and documented in the page's methodology accordion.