The Causal Uncertainty Principle
Fuente:
arXiv
Guardado en:
| Autor principal: | |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866909930919821312 |
|---|---|
| author | Reidpath, Daniel D. |
| author_facet | Reidpath, Daniel D. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_22649 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Causal Uncertainty Principle Reidpath, Daniel D. Applications Information Theory 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. |
| title | The Causal Uncertainty Principle |
| topic | Applications Information Theory |
| url | https://arxiv.org/abs/2511.22649 |