statfidelity: Audit Statistical Fidelity of AI-Mediated Official Statistics
Provides deterministic tools for auditing whether artificial
intelligence systems preserve the numerical, semantic, contextual,
temporal, geographic, unit, provenance, revision, transformation, and
uncertainty properties of official statistics. Structured reference
statistics and machine-generated claims can be compared with
non-compensatory critical-error rules, weakest-link and geometric fidelity
summaries, provenance graphs, and portable SHA-256 proof bundles. The
package also provides bounded connectors for official Eurostat, World Bank,
OECD, United Nations SDG, United Kingdom Office for National Statistics,
and United States Bureau of Labor Statistics application programming
interfaces, plus an extensible HTTPS JSON API registry with session-only
API-key support. Prompt perturbation, statistical red-team generation,
minimal-pair tests, and starter benchmark data support reproducible
evaluation of generative, retrieval-augmented, and agentic statistical
systems. An embedded alignment layer maps claim-level controls to relevant
activities of the Generic Statistical Business Process Model (GSBPM) 5.2,
including Analyse, Disseminate, Evaluate, Quality Management, and Metadata
Management. No specific model provider is required.
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