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

Akio Hotta

No k9rzb_v1, SocArXiv from Center for Open Science

Abstract: 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 as J = 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 markets Anticipatory Suppression and So… . Keywords: matching markets, safety, transparency, algorithmic fairness, experimentation

Date: 2025-09-23
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:k9rzb_v1

DOI: 10.31219/osf.io/k9rzb_v1

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