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Quality-Driven Propagation and Adaptive Reopening: A Falsifiable Hypothesis Framework for Epistemic–Propagation Coupling and Reopening After Lock-In in Networked Information Systems

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)
Complex Network Analysis Techniques

Abstract

Dieses theoretische Hypothesenpapier entwickelt einen falsifizierbaren Rahmen für Quality-Driven Propagation, Epistemic–Propagation Coupling und Adaptive Reopening in vernetzten Informationssystemen. Ausgangspunkt ist die Beobachtung, dass sich Informationen nicht ausschließlich aufgrund ihrer epistemischen Qualität verbreiten. Sichtbarkeit, Autorität, Wiederholung und Netzwerkposition können die Propagation eines Signals unabhängig von seiner inhaltlichen Qualität beeinflussen. Das Papier führt deshalb Propagation Dynamics als allgemeinen Rahmen für die Untersuchung der Ausbreitung übertragbarer Signale in Netzwerken ein. Als zentraler vorgeschlagener Messgegenstand wird Epistemic–Propagation Coupling (Γ_EQ) definiert: die statistische Kopplung zwischen Propagationsstärke und unabhängig bewerteter epistemischer Signalqualität, nachdem Einflüsse wie Sichtbarkeit, Autorität, Validierungsstatus und Netzwerkposition berücksichtigt wurden. Darauf aufbauend unterscheidet der Ansatz zwischen effizienter Konvergenz und pathologischem Lock-in. Adaptive Reopening bezeichnet dabei die Fähigkeit eines Systems, nach einer Verengung wieder Quellenvielfalt, unabhängige Validierung, alternative Propagationspfade, Sensitivität gegenüber Gegenbelegen und eine stärkere Kopplung zwischen Qualität und Propagation zurückzugewinnen. Das Manuskript formuliert fünf falsifizierbare Hypothesen, ein minimales mathematisches Netzwerkmodell, mögliche beobachtbare Größen sowie ein empirisches Validierungsprogramm mit Nullmodellen und expliziten Falsifikationsbedingungen. Memetische und kulturelle Diffusion werden lediglich als mögliche Anwendungsbereiche betrachtet. Der Rahmen ist allgemeiner angelegt und soll prinzipiell auch auf wissenschaftliche Kommunikation, institutionellen Wissenstransfer, organisationales Lernen, technische Fehlerpropagation und verteilte Sensornetzwerke anwendbar sein. Status: Version 2.1 — Theoretical / Hypothesis Preprint. Es wird keine empirische Validierung beansprucht. Das Manuskript ist nicht peer-reviewed und dient als theoretische Grundlage für die geplante Forschungsarchitektur von BenchEWS Studio 3.0 ECHO. Die beschriebenen Konzepte sind nicht Bestandteil von BenchEWS Studio 2.0. Keywords:Quality-Driven Propagation; Propagation Dynamics; Epistemic–Propagation Coupling; epistemische Qualität; unabhängige Validierung; Information Cascades; Social Learning; Network Epistemology; Netzwerkdynamik; Lock-in; Adaptive Reopening; Goodhart Dynamics; Authority Bias; Visibility; komplexe adaptive Systeme; wissenschaftliche Kommunikation; Informationsdiffusion; falsifizierbare Hypothesen; BenchEWS; ECHO Description This theoretical hypothesis paper develops a falsifiable framework for Quality-Driven Propagation, Epistemic–Propagation Coupling, and Adaptive Reopening in networked information systems. The framework starts from the observation that information does not propagate solely in proportion to its epistemic quality. Visibility, authority, repetition, and network position can sustain the propagation of a signal independently of how well supported it is. The paper therefore introduces Propagation Dynamics as a general framework for studying how transmissible signals move through networks. Its central proposed construct is Epistemic–Propagation Coupling (Γ_EQ): the degree to which propagation strength is statistically associated with independently assessed epistemic signal quality after accounting for factors such as visibility, authority, validation status, and network position. Building on this construct, the framework distinguishes between efficient convergence and pathological lock-in. Adaptive Reopening describes the capacity of a propagation system, following lock-in or perturbation, to regain source diversity, independent validation, alternative propagation pathways, sensitivity to counter-evidence, and stronger coupling between epistemic quality and propagation. The manuscript formulates five falsifiable hypotheses, a minimal mathematical network model, candidate observables, and an empirical validation programme including explicit null models and failure conditions. Memetic and cultural diffusion are treated only as possible application domains. The general framework is intended to also cover scientific communication, institutional knowledge transfer, organizational learning, technical fault propagation, and distributed sensor networks. Status: Version 2.1 — Theoretical / Hypothesis Preprint. No empirical validation is claimed or implied. The manuscript has not been peer-reviewed and is intended as theoretical groundwork for the planned BenchEWS Studio 3.0 ECHO research architecture. None of the proposed constructs are implemented in BenchEWS Studio 2.0. Keywords:Quality-Driven Propagation; Propagation Dynamics; Epistemic–Propagation Coupling; epistemic quality; independent validation; information cascades; social learning; network epistemology; network dynamics; lock-in; adaptive reopening; Goodhart dynamics; authority bias; visibility; complex adaptive systems; scientific communication; information diffusion; falsifiable hypotheses; BenchEWS; ECHO

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