The Integrity Gap Model: A Structured Framework for Measuring Specification-Behavior Divergence in Governed Systems

Version 3 of the Integrity Gap Model (IGM), a practitioner whitepaper introducing a structured framework for measuring the gap between what governed systems specify and what they actually do. The model defines five core variables — Integrity Gap (ΔI), Masking (M), Verification Threshold (θ), Ecology (ε), and Effort Asymmetry (ρ) — and applies them to cybersecurity compliance governance. Key additions in v3: four-category ΔI taxonomy (adding iatrogenic ΔI), specification assessment protocol, M↑ diagnostic machinery, three-type proxy failure taxonomy differentiating the governance horizon from Goodhart and Campbell, three mechanism-level predictions carrying the scale-invariant hypothesis, and the detection-clearance separation principle. The paper commits to the strong version of the scale-invariant hypothesis — structural identity across governed systems from code to culture — and specifies falsification criteria for each claim. Developed from a decade of professional practice in cybersecurity, information security, and ISO governance.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-27
DOI
https://doi.org/10.5281/zenodo.19242795
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
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article

The Integrity Gap Model: A Structured Framework for Measuring Specification-Behavior Divergence in Governed Systems

Houssam Badi
Zenodo (CERN European Organization for Nuclear Research)
Information and Cyber Security
article

The Integrity Gap Model: A Structured Framework for Measuring Specification-Behavior Divergence in Governed Systems

Houssam Badi
article en

Abstract

Version 3 of the Integrity Gap Model (IGM), a practitioner whitepaper introducing a structured framework for measuring the gap between what governed systems specify and what they actually do. The model defines five core variables — Integrity Gap (ΔI), Masking (M), Verification Threshold (θ), Ecology (ε), and Effort Asymmetry (ρ) — and applies them to cybersecurity compliance governance. Key additions in v3: four-category ΔI taxonomy (adding iatrogenic ΔI), specification assessment protocol, M↑ diagnostic machinery, three-type proxy failure taxonomy differentiating the governance horizon from Goodhart and Campbell, three mechanism-level predictions carrying the scale-invariant hypothesis, and the detection-clearance separation principle. The paper commits to the strong version of the scale-invariant hypothesis — structural identity across governed systems from code to culture — and specifies falsification criteria for each claim. Developed from a decade of professional practice in cybersecurity, information security, and ISO governance.

Zenodo (CERN European Organization for Nuclear Research)
Healthcentric Advisors (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 7%
Information and Cyber Security
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