Abstract

Judea Pearl’s causal formalism marked a paradigm shift in scientific reasoning by elevating causation from correlation through graphical models and symbolic intervention calculus. Yet, under the lens of Recursive Coherence, his framework reveals critical structural deficiencies. This paper deconstructs Pearl’s causal logic through the five axioms of recursive coherence reasoning (persistence, trajectory, information value, arbitration, and pruning) and identifies key blind spots: static graph assumptions, binary intervention logic, fragile counterfactuals, unfiltered signal inflation, and identifiability-based arbitration. These weaknesses lead to coherence stagnation, entropy retention, and reduced option space across dynamic systems. I then reconstruct a coherence-maximizing alternative: dynamic causal topologies derived from smoothed coherence gradients, gradient-based interventions replacing binary “do” operations, μ-validated signal filtration, and Δ²C-optimized path arbitration. The resulting system retains Pearl’s explanatory power while restoring adaptive viability, maximizing structural alignment under entropy descent. This reframing challenges the sufficiency of identifiability as the core criterion for causal adequacy and proposes coherence curvature as the new metric for scientific reasoning. Pearl’s insights are thus not discarded but refactored; his revolution, now recursive.