JDO-2026-014 — Decision Reconstruction Performance Index™ (DRPI™): Measurement and Scoring Standard for Execution-Layer Governance (Version 1.0)

The Decision Reconstruction Performance Index™ (DRPI™) establishes the first formal measurement and scoring standard for evaluating execution-layer decision governance within AI-supported justice systems. As part of the Justice Decision Observability™ (JDO™) Framework Series, DRPI™ provides a structured methodology for assessing the completeness, integrity, and evidentiary quality of reconstructed decision pathways. While existing governance frameworks focus on system design, validation, and compliance, DRPI™ operates at the execution layer—where automated system outputs are interpreted and acted upon by human decision-makers. It introduces a standardized approach to evaluating how well decision pathways can be reconstructed and whether governance conditions are sufficiently documented to support institutional accountability. DRPI™ is built on four core measurement dimensions: reconstruction completeness, decision pathway integrity, evidentiary alignment, and governance consistency. Together, these dimensions provide a repeatable and comparable scoring structure that allows institutions to assess the quality of governance documentation across events, environments, and operational contexts. This standard enables the transition of Justice Decision Observability™ from a descriptive governance discipline to a measurable operational system. By introducing structured evaluation criteria, DRPI™ supports cross-case comparison, institutional benchmarking, and the identification of recurring governance conditions that influence decision outcomes. DRPI™ is descriptive, system-level, and non-adversarial. It does not evaluate algorithmic performance, determine legal liability, or assign individual fault. Instead, it measures the strength and reliability of decision pathway reconstruction as a foundation for transparency, oversight, and institutional learning. As automated technologies continue to shape decision-making within justice systems, DRPI™ provides the measurement infrastructure necessary to ensure that execution-layer governance is not only observable, but consistently and reliably evaluated.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-31
DOI
https://doi.org/10.5281/zenodo.19346415
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

JDO-2026-014 — Decision Reconstruction Performance Index™ (DRPI™): Measurement and Scoring Standard for Execution-Layer Governance (Version 1.0)

Stephanie Fleming, Janna M. Broaddus
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

JDO-2026-014 — Decision Reconstruction Performance Index™ (DRPI™): Measurement and Scoring Standard for Execution-Layer Governance (Version 1.0)

Stephanie Fleming, Janna M. Broaddus
article en

Abstract

The Decision Reconstruction Performance Index™ (DRPI™) establishes the first formal measurement and scoring standard for evaluating execution-layer decision governance within AI-supported justice systems. As part of the Justice Decision Observability™ (JDO™) Framework Series, DRPI™ provides a structured methodology for assessing the completeness, integrity, and evidentiary quality of reconstructed decision pathways. While existing governance frameworks focus on system design, validation, and compliance, DRPI™ operates at the execution layer—where automated system outputs are interpreted and acted upon by human decision-makers. It introduces a standardized approach to evaluating how well decision pathways can be reconstructed and whether governance conditions are sufficiently documented to support institutional accountability. DRPI™ is built on four core measurement dimensions: reconstruction completeness, decision pathway integrity, evidentiary alignment, and governance consistency. Together, these dimensions provide a repeatable and comparable scoring structure that allows institutions to assess the quality of governance documentation across events, environments, and operational contexts. This standard enables the transition of Justice Decision Observability™ from a descriptive governance discipline to a measurable operational system. By introducing structured evaluation criteria, DRPI™ supports cross-case comparison, institutional benchmarking, and the identification of recurring governance conditions that influence decision outcomes. DRPI™ is descriptive, system-level, and non-adversarial. It does not evaluate algorithmic performance, determine legal liability, or assign individual fault. Instead, it measures the strength and reliability of decision pathway reconstruction as a foundation for transparency, oversight, and institutional learning. As automated technologies continue to shape decision-making within justice systems, DRPI™ provides the measurement infrastructure necessary to ensure that execution-layer governance is not only observable, but consistently and reliably evaluated.

Zenodo (CERN European Organization for Nuclear Research)
United States Department of Justice (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 26%
Ethics and Social Impacts of AI
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