090°Open data
Open datasets, fully documented — searchable here, and readable by any LLM.
8 datasets
Global Gender Labor Gap Signals (derived)
Value-added gender labour-market signals from free ILOSTAT modelled estimates: female-minus-male unemployment, participation and employment gaps with 10-year convergence trends, convergence flags, 3-sigma anomaly flags and cross-country gap ranks across ~190 countries. All computation is local pandas/numpy; no paid models or APIs.
Global Living-Standards Signals (derived)
Yearly global living-standards signals from IMF DataMapper GDP per capita at purchasing power parity (PPPPC, ~190 economies, 1980 ->, WEO projections as published): 5- and 10-year changes, 10-year OLS trend slopes, 3-sigma anomaly flags, linear 5-year forecasts, 10-year income z-scores, per-year global income ranks, high/low-income flags and a catch-up (convergence) flag. The living-standards lens on the world economy — income levels, not growth rates. Companion to imf-global-real-gdp-growth-signals (rates) and global-debt-signals (fiscal stock). All rows carry canonical country_code labels. Raw indicator: International Monetary Fund, DataMapper.
Poverty & Inequality Signals (derived)
Country-level signals derived from World Bank poverty and inequality indicators (Gini index, poverty headcount at $3.00 and $4.20 a day, 2021 PPP): 10-year point changes, OLS trend slopes over trailing survey years, 3-sigma anomaly flags, 5-year linear-extrapolation forecasts, per-year cross-country ranks, a poverty-improvement flag and a high-inequality flag. All rows are normalized to ISO alpha-3 country_code so they join cleanly with country macro data. Raw data: World Bank Poverty and Inequality Platform (keyless API, non-commercial terms).
Productivity-Pay Gap Signals (derived)
Quarterly signals derived from BLS productivity and costs data (redistributed by FRED, 1947 ->): 30-quarter annualized change volatility, 1-quarter momentum, year-over-year change, 3-sigma anomaly flags vs a trailing 12-quarter baseline, naive-drift 1-quarter forecasts, a per-quarter cross-series volatility rank, the real pay-minus-productivity gap (both rebased to 1947 = 100 — the decoupling gauge) and a 10-year gap z-score (the decoupling-regime gauge). All rows are normalized to country_code USA so they join cleanly with US macro data. Raw series: Federal Reserve Bank of St. Louis (FRED); underlying data: U.S. Bureau of Labor Statistics.
UN SDG Global Database
Proportion of population below international poverty line (%) SDG indicator SI_POV_DAY1 (SDG goal 1). Source: UN SDG Global Database. Rows are geo-area x year x disaggregation dimensions (sex, age, location/urban-rural where published).
World Bank
Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.
Poverty gap at $3.00 a day is the mean shortfall in income or consumption from the poverty line of $3.00 a day at 2021 international prices (2021 PPP), counting the non-poor as having zero shortfall, expressed as a percentage of the poverty line. It reflects the depth of poverty as well as its incidence. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.
Poverty headcount ratio at $3.00 a day is the percentage of the population living on less than $3.00 a day at 2021 international prices (2021 PPP). As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.
Once today's free allowance is used up, AI features can run on your own provider account.
Kept in this browser tab only (cleared when you close it) and sent with each AI request. Our servers use it for that request and never store or log it.