Causationto

Causationto is a neologism used in discussions of causal reasoning to describe a framework for representing and reasoning about causal influence as a directional transfer from causes to effects within complex systems. The term blends causation with the directional sense of to, signaling an emphasis on the arrow of causation rather than mere association. As a concept, causationto is not tied to a single formal theory but can be instantiated within existing causal formalisms such as directed graphs, potential outcomes, or dynamical models.

Concept and interpretation: It highlights how causal power propagates through networks, across levels and through mediating mechanisms, and it supports distinguishing which parts of a system actively transmit a causal influence to outcomes of interest. In practice, a causationto analysis may trace a chain of effects from a treatment to downstream outcomes, accounting for mediators and feedback, and comparing different interventions by their downstream causal reach.

Applications: used in policy evaluation to assess how interventions yield outcomes, in epidemiology to map pathways of risk, and in AI interpretability to explain decisions in terms of causal pathways. It is compatible with standard tools like causal graphs and potential outcomes but emphasizes directional tracing of effects.

Criticism and relation: Some scholars argue that causationto adds little beyond established notions of causal influence and risk of vagueness if not formalized. Proponents emphasize its usefulness as a clarifying heuristic for distinguishing causal flow from mere correlation. The term remains obscure outside specific academic circles and is not widely adopted in mainstream causal inference literature.