AIO
AIO 10003 · Person Eval

Value-priority measurement of persons & organizations

We measure value priorities revealed in public records (decisions, actions, statements) as rankings on a domain × 45-cell grid, and report the distance between professed (words) and revealed (actions).

The goal

AIO 10003 — analyze an individual’s value priorities from public records

The standard number is the goal statement. The digits 1·00·0·3 say whose values, in which domain, and which action this document covers.

1
Subject

Individual — persons (and organizations with public records)

00
Domain

Common — domain-independent

0
Serial

Base document

3
Action

Analyze — measure revealed priorities

What this standard defines event collection (pre-registered sampling frame, source URLs, confidence grades), pair coding (genuine conflicts only, i≻j), ranking estimation (Bradley–Terry / Plackett–Luce with confidence intervals), professed–revealed gap reporting, and verified/unverified · observed/inherited/estimated labeling. What it does not define whether a person, organization, or value is good or bad. These measurements describe priority structure only — they never judge (non-normative). All evidence comes from already-public records, and subjects may contest any finding; corrections are published with sources.

Where it sits

Step 3 of the integrity loop — Analyze (individual axis)

1Set2Log3Audit4Apply

AIO 10003 is the first published standard on the individual (1) subject axis. The individual-axis setting (10001) and recording (10002) standards are planned stages; the same analysis cell on the organization (2) axis holds AIO 20003 · Benchmark.

The document

How we measure

① Event collection

Public records (decisions, actions) are collected within a pre-registered sampling frame. Every event carries source URLs and a confidence grade.

② Pair coding

We conservatively code only genuine conflicts — which value was sacrificed for which (i≻j). Mere mentions are not evidence.

③ Ranking estimation

Bradley–Terry / Plackett–Luce models estimate latent rankings per cell with confidence intervals, suited to sparse, unbalanced observations.

④ Professed–revealed gap

We report the distance between professed rankings (words) and revealed rankings (actions) — the core output, a measurement, not a verdict.

Honesty rules
  • Public records never cover all value pairs — covered pairs are "observed"; the rest are honestly labeled inherited, estimated, or no-data.
  • Only cells meeting verification conditions (coder reliability, transitivity, minimum observations) are marked "verified" — we never call an entire subject "verified."
  • A professed–revealed gap is not a disqualifier — it is a reported finding.
Tools for this goal

Measurement status — targets in progress

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Contribute

Contest and respond

Subjects and their organizations may contest any finding at info@aioq.org; corrections are published with sources. Suggestions for measurement targets are welcome at the same address.

AIO 10003 Person Eval — value-priority measurement of persons & organizations | AIO