Global Humanity Update 2026: five signals, one cautious reading
An evidence-led 2026 reading of suicide mortality, homicide, freedom of expression, child labour and consumption-based carbon emissions—with dates and limits visible.
Read analysis →Evidence / analysis
Read beyond the signal.
Original analysis connects the numbers to their definitions, dates, coverage and uncertainty. Every article links to its primary evidence and explains where interpretation must stop.
Start with the sources.
Explore the dashboard, country profiles and indicators, then choose an action.
Why indicators from different years cannot form one photograph
A practical guide to comparing public indicators whose latest observations come from different years.
Read analysis →Missing data is not zero: the most important rule on this site
Why blank, stale and incomplete observations must not be converted into reassuring zeros.
Read analysis →Reading suicide statistics responsibly
What suicide mortality rates reveal, what they hide, and how to discuss them without turning suffering into a ranking.
Read analysis →Homicide data: count, rate and context are three different stories
How to read intentional homicide statistics without confusing population rates, absolute losses and reporting coverage.
Read analysis →Child labour in 2024: progress that did not meet the promise
What the latest ILO–UNICEF estimates show about the decline in child labour, hazardous work and the regions still carrying the heaviest burden.
Read analysis →Freedom of expression: how to read an expert-coded index
A plain-language guide to the V-Dem freedom-of-expression index, its 2026 warning signal and its uncertainty.
Read analysis →Consumption-based versus territorial CO₂: why trade changes the map
How imported and exported emissions change a country’s carbon footprint—and why this physical measure needs its own interpretation.
Read analysis →Composite indexes: useful map, dangerous verdict
Why composite scores can orient attention while hiding assumptions about normalization, weights, missing data and moral trade-offs.
Read analysis →Regional averages: coverage must come before comparison
Why a regional average without a coverage fraction can be more misleading than no regional number at all.
Read analysis →Methods stay open.
See every transformation, weight, aggregation rule and limitation used by the observatory.