Threshold Dynamics in Social Contagion: How Bifurcation Structure, Re-entrant Phases, Correlated Noise, Coalition Catalysis, and Monoculture Lock-In Jointly Define a Candidate Framework for Systemic Social Risk

Social systems routinely exhibit outcomes that appear discontinuous with their inputs: a school population tips from low to high substance use; online hate content spreads system-wide after a long quiescent period; a labor market uniformly rejects candidates from certain demographic groups even though no single employer intended discrimination. This paper argues that a structurally coherent pattern—call it *threshold-governed lock-in*—runs across five recent arXiv preprints spanning physics.soc-ph, econ.TH, and cs.CY. The pattern is not derived from a single shared formalism; this is a heuristic reading that identifies analogous mechanisms across domains. The candidate framework has three moving parts. First, social contagion processes—whether substance use escalation, hate-content spread, or collective error in estimation—are governed by bifurcation points and threshold phases rather than smooth dose-response relationships. Second, correlation structure in the environment (correlated noise, shared algorithmic vendors, common training data) amplifies rather than averages out individual errors, converting local susceptibility into system-wide lock-in. Third, coalition formation and intermediary design are the candidate levers for escaping sub-optimal equilibria, but both are fragile: coalitions continuously reconfigure, and intermediary incentives are difficult to align. Sources span observational analysis of 3 million hiring records [corpus:arxiv:2605.27371], a controlled online experiment with 600 participants [corpus:arxiv:2605.30522], a bifurcation-theoretic epidemic model [corpus:arxiv:2606.12564], a coalescence-fragmentation model of hate spread [corpus:arxiv:2605.21129], and a game-theoretic network model of coalition catalysis [corpus:arxiv:2606.07584]. The primary falsification path: if correlated environmental signals do not amplify lock-in beyond what independent-signal baselines predict, the correlation-amplification mechanism collapses and the framework requires revision. The abstract reports findings from preprints, none of which are peer-reviewed. ---

Authorship: Saluca Agentic AI Research Team (Saluca LLC). AI-drafted from arXiv preprint corpus on the date in the filename.

Cited arXiv preprints: 2605.21129, 2605.25192, 2605.26703, 2605.27371, 2605.29621, 2605.29749, 2605.30169, 2605.30522, 2605.31072, 2606.02348, 2606.05954, 2606.07584, 2606.09083, 2606.10631, 2606.11116, 2606.11692, 2606.12260, 2606.12564