REBORN — What If You Were Born Again?
REBORN is a weighted life simulator that assigns you a randomized human identity — country, gender, family, wealth, health, education, and life expectancy — based on real global statistics from the World Bank, WHO, UNICEF, UNESCO, and the UN Population Division (WPP 2024). Nothing is random; everything is weighted by real-world data.
How the simulation works
- Country selection — Weighted by each country's actual annual newborn count (UN WPP 2024). A baby born right now is overwhelmingly likely to be Indian, Nigerian, Pakistani, or Chinese. The dataset covers all 195+ sovereign states and territories.
- Gender — Weighted 51.2% male / 48.8% female to match the global sex ratio at birth. Downstream outcomes (education, life expectancy) are adjusted by each country's Gender Inequality Index (UNDP).
- Family structure — Determined by country-specific UNICEF/DHS rates for orphan share, institutional care, single-parent households, extended families, and two-parent households.
- Siblings — Sampled from a fat-tailed distribution centered on the country's average family size (UN WPP 2024).
- Wealth & income — Bottom three brackets use real World Bank Poverty and Inequality Platform headcount ratios at $3.00, $4.20, and $8.30/day (2021 PPP). Upper brackets are derived from each country's Gini coefficient. Income is modeled with a log-normal distribution and converted through country-specific PPP factors (World Bank ICP 2023).
- Health & disability — 94% of babies are born healthy. The remaining 6% are distributed across 13 categories of congenital conditions, adjusted by country disability rate and wealth bracket.
- Access to basics — Clean water, electricity, internet, and education access are pulled from country data and adjusted for disability and poverty, scaled by an income-group mitigation factor.
- Education — Base score combines country education access with a tertiary anchor. Adjusted by wealth, gender (with Gender Inequality Index penalty), health, family structure, and sibling count in poverty. Score maps to level from "no formal education" to "university degree."
- Life expectancy — Starts at the country baseline (WHO) and is adjusted by wealth, health (with a healthcare-quality multiplier for the country's income tier), gender, education, water access, and family structure. Condition-specific caps override generic penalties.
- Anomaly detection — Positive (Statistical Miracle, Against All Odds, Defying the System, Medical Miracle, One in a Million, The 0.001%, Supercentenarian, Rare Family) and negative (Fallen Through the Cracks, Stolen Future, Wasted Privilege, A Life Barely Begun, The Invisible, Compounding Cruelty) tags flag statistically extraordinary combinations.
Data sources
- World Bank Open Data — population, income groups, poverty rates, education enrollment, infrastructure access
- WHO Global Health Observatory — life expectancy, disability rates, disease prevalence
- UNICEF Data — orphan rates, child protection, family structure
- UNESCO Institute for Statistics — education completion, literacy, tertiary enrollment
- UN Population Division (WPP 2024) — birth rates, family size, demographic projections
- UNDP Human Development Reports — Gender Inequality Index
- World Bank ICP 2023 — Purchasing Power Parity factors
- DHS Program — single-parent rates, household composition
Read more
REBORN requires JavaScript to run the interactive simulator. This page describes what the app does and how the underlying model works.
This is not fiction. This is probability.