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The mathematical machinery of causal inference: from data to decision advantage.

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Bibliographic Details
Title: The mathematical machinery of causal inference: from data to decision advantage.
Authors: Elin, Stephen Matthew (AUTHOR) stephen.elin@pm.me
Source: Intelligence & National Security. Nov2025, p1-31. 31p. 24 Illustrations.
Subject Terms: *CAUSAL inference, *CAUSAL models, *OPERATIONS research, *QUANTITATIVE research, *EMPIRICAL research, *PATTERN perception
Abstract: Quantitative intelligence analysis often leans on pattern recognition; in adversary-shaped settings, such correlations can be engineered. Building on Judea Pearl’s structural causal models – originally developed for natural data-generating processes – this study makes identification, not estimation, the gate to credible claims. Across operational cases, it clarifies when effects are recoverable from observational data and when additional leverage is required. The framework extends to sequential and multi-agent settings – as developed by Elias Bareinboim and colleagues – in which strategies are modelled as interventions. The result is an explicit, testable mapping from action to outcome that turns uncertain signals into actionable intelligence and delivers decision advantage. [ABSTRACT FROM AUTHOR]
Database: Academic Search Index
Description
Abstract:Quantitative intelligence analysis often leans on pattern recognition; in adversary-shaped settings, such correlations can be engineered. Building on Judea Pearl’s structural causal models – originally developed for natural data-generating processes – this study makes identification, not estimation, the gate to credible claims. Across operational cases, it clarifies when effects are recoverable from observational data and when additional leverage is required. The framework extends to sequential and multi-agent settings – as developed by Elias Bareinboim and colleagues – in which strategies are modelled as interventions. The result is an explicit, testable mapping from action to outcome that turns uncertain signals into actionable intelligence and delivers decision advantage. [ABSTRACT FROM AUTHOR]
ISSN:02684527
DOI:10.1080/02684527.2025.2574789