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The Causal Uncertainty Principle

Published: November 27, 2025 | arXiv ID: 2511.22649v1

By: Daniel D. Reidpath

Potential Business Impact:

Order of study steps limits what findings can apply.

Business Areas:
A/B Testing Data and Analytics

This paper explains why internal and external validity cannot be simultaneously maximised. It introduces "evidential states" to represent the information available for causal inference and shows that routine study operations (restriction, conditioning, and intervention) transform these states in ways that do not commute. Because each operation removes or reorganises information differently, changing their order yields evidential states that support different causal claims. This non-commutativity creates a structural trade-off: the steps that secure precise causal identification also eliminate the heterogeneity required for generalisation. Small model, observational and experimental examples illustrate how familiar failures of transportability arise from this order dependence. The result is a concise structural account of why increasing causal precision necessarily narrows the world to which findings apply.

Page Count
7 pages

Category
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