Abstract
This disclosure establishes prior art for a computer-implemented system and method for privacy-first, values-aligned relational matching and community formation. The system is defined by a fixed operational sequence: private reflection, behavioral observation, simulated interaction modeling, bilateral correction, and conditional identity revelation. Behavioral modeling is performed on non-presentational behavioral signals—user-generated data produced in the absence of a perceived audience—thereby reducing incentive for strategic self-representation and mitigating data distortion common in existing social and dating platforms.
A Behavioral Pattern Recognition Engine (BPRE) generates compatibility distributions grounded in established relational research frameworks. A Simulation and Correction Interface (SCI) presents interpretive models of potential interaction dynamics independently to each participant, enabling human-in-the-loop correction prior to identity exposure. Compatibility thresholds require convergence across statistical alignment and bilateral correction agreement, ensuring that user-confirmed interpretive coherence is a binding condition of connection.
A Values Alignment Index (VAI) dynamically integrates declared and observed signals, while a Connective Routing Layer (CRL) facilitates community-level matching based on complementary gifts and needs. A Community Body Architecture (CBA) enables self-hosted, federated, or governance-bound deployment, structurally preventing third-party control or transfer of relational data.
The system produces a convergence property over time between perceived identity and observed behavior, functioning not only as a matching mechanism but as a continuous identity-alignment system. This disclosure distinguishes itself from prior art through its non-presentational data domain, pre-exposure bilateral correction paradigm, and enforcement of a reflection-to-connection sequence that makes both deception and self-deception structurally more difficult.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Walker, Joseph JM, "System and Method for Relational Matching Using Non-Presentational Behavioral Signals with Pre-Exposure Bilateral Model Correction", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/10031