Universal Human Project — Framework & Measurement Sandbox

Core framework

Declarative structure required for consistent measurement and comparability. Entities and definitions are canonical — do not conflate metric-level values with domain-level indices. Calculation rules are deterministic and auditable.

Domain	Parts / Key metrics	Purpose
Unity — Humans	Life satisfaction; civic participation; inequality indices; social cohesion scores	Measure human-centered social outcomes and prosocial behaviors
Unity — HCI	Accessibility compliance; usability trust; time-to-task; bias & fairness audits	Measure human–technology interaction quality and trust
Health — Physical	Life expectancy; activity prevalence; chronic disease rates	Measure population physical health outcomes and mobility
Health — Mental	Wellbeing indices; prevalence of clinical conditions; resilience metrics	Measure mental health and psychosocial functioning
Progress	Composite productivity index; GDP per capita growth; AI capability benchmarks (LLM benchmarks as examples); service/access satisfaction	Measure growth and productivity as defined by domain improvements and external benchmarks

Metric catalog (sample)

Metric	Type	Range / Unit

Normalization rules encoded per metric: {method: "minmax"|"zscore", invert: boolean, baseline:[min,max], weight:0-1}

Dashboard — live sandbox

UHP Composite Index

Composite across domain scores and external productivity benchmarks

—

scaled 0–100

Domain trend summary

Slope of last 12 months, direction, and magnitude

Metric weights & live recalculation

Alerts & thresholds

Threshold definitions applied per metric. Triggered alerts appear here.

Designer — add / edit metric

Schema, formulas, and sample API

Metric JSON schema (canonical). Use for ingestion pipelines and validators.

{
  "metric_id":"string",
  "label":"string",
  "domain":"humans|hci|physical|mental|progress",
  "unit":"string",
  "norm":{"method":"minmax|zscore","invert":false,"baseline":[min,max]},
  "weight":0.0,
  "timeseries":[{"date":"YYYY-MM-DD","value":number}],
  "last_updated":"ISO8601"
}

Computation formulas (deterministic)

Normalize metric value: if minmax => (v-min)/(max-min). If invert => 1 - normalized.
Domain score at time t: weighted mean of normalized metric values within domain using metric weights (sum weights > 0).
Progress score: weighted mean of domain scores and external productivity benchmarks (e.g., GDP growth normalized, AI benchmark score normalized).
UHP index: composite scaling to 0–100, transparent weights; store both raw and scaled values.
Trend detection: compute linear slope on last N points; publish slope and p-value (if desired) for audit.

Governance, ethics, and data policy (directive)

Open data publication policy: publish aggregated indices and formulas. Do not publish personally identifying timeseries. Use privacy-preserving aggregation. Version metrics and schemas. Require provenance for each data source (authority, timestamp, collection method). Publish change logs and computation code.

Governance primitives

Immutable metric definitions (versioned)
Reproducible computation (export of inputs + code)
Independent audit (third-party reproducibility tests)
Data access tiers: public / research / restricted

Ethics checklist

Bias assessment in HCI metrics
Equity-weighted reporting for populations
Safety review for AI benchmark usage
Consent & DPIA for collected individual-level data