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

Version 2 — revised in response to an external structural review and an automated critique pass. See "Response to Review" appendix in the PDF for the change log.

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, and the analogies are argued at the level of vocabulary and structural family resemblance rather than shared mathematical objects. 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 in controlled experiments, 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

AI disclosure. This work was produced with an agentic AI research apparatus operated by Saluca Labs. The apparatus drafted, searched and analysed under direction. Cristian Ruvalcaba is the human author and is accountable for the content. No AI system is listed as an author or contributor, because authorship entails accountability that a model cannot hold; this disclosure is the credit, and it is deliberately the whole of it.