Do Sunspot Cycles Causally Affect Social Tensions and Population Harm in Developing Countries?

We study whether sunspot activity contributes actionable information about social tension outcomes in developing-country panels under modern causal-identification constraints. Building on staggered-adoption estimand logic, we formulate an eventized continuous-dose aggregation framework with explicit support and contamination diagnostics. We then introduce a robust-null acceptance predicate that jointly audits dataset harmonization, exposure-version sensitivity, and placebo boundedness, and we connect causal interpretation to constrained subset deployment through a comparator-parity utility decomposition. Formal analysis establishes identification and admissibility results for the weighted estimand, robust-null rule, and subset utility identity. Validation artifacts with symbolic theorem checks, dynamic event-time diagnostics, lattice stress tests, and parity-calibrated forecasting outputs show coherent estimator mechanics and conservative mixed-support interpretation under uncertainty. The key contribution is an auditable inference-to-decision workflow that preserves negative evidence while identifying where bounded, subset-specific utility can remain defensible.