Anticipatory Suppression and Social Cost in Dating Platforms: A JX Framework Whitepaper

Dating platforms face a critical tension: maximizing engagement can conflict with safety, fairness, and user agency. This paper presents Transdisciplinary Equilibrium (JX), a composite social–cost objective that makes this tension measurable and optimizable.We formalize social cost asJ = αE + βS + γA,where E captures rejection-driven harm (e.g., ghosting, ignored messages), S measures exposure asymmetry (e.g., Gini of impressions, top-decile share), and A quantifies anticipatory suppression (non-initiation, delete-after-view, view→message drop). An optional interaction term,Jη = J + η(E·S),models compounding harms when rejection and asymmetry reinforce each other.Contributions. Our framework delivers:(i) a Metric DAG linking product levers to auditable outcomes,(ii) estimators and experimental designs for platform evaluation,(iii) a safety workflow and algorithmic transparency interface, and(iv) guardrailed calibration of (α, β, γ, η) enabling measurable reductions in social cost while preserving user agency.Impact. JX provides proxy-based measurement, lever-to-metric mapping, and auditable trade-off analysis — a practical blueprint for safer, fairer matching marketsAnticipatory Suppression and So….Keywords: matching markets, safety, transparency, algorithmic fairness, experimentation