Finite-Capacity Prospect Theory: State-Dependent Risk Preferences under Resource, Attention, and Boundary-Risk Constraints

This paper is also published in SocArXiv: https://doi.org/10.31235/osf.io/pj43k_v1 Official website: distinctiontheory.orgPublic portal for the start guide, papers, claim status, failure registry, prior-art boundary, and citation resources. Canonical GitHub repository:https://github.com/yiningwu-research/Distinction-Theory This record contains FDS-E1: Finite-Capacity Prospect Theory, a behavioral-economics bridge paper in the Distinction Theory / Active Finite Distinction Systems research programme. The paper proposes that the central parameters of Prospect Theory are not fixed irrationality constants, but state-dependent finite-system control variables: (λt, αt, γt) = f(Fefft, Ct, Bt, θt). Loss aversion, reference dependence, and probability weighting are modeled as boundary-risk management responses of finite agents operating under resource scarcity, limited attention, limited distinguishability, and finite update capacity. The paper introduces a vector resource-buffer model, perceived boundary distance, event-class-dependent probability weighting, and a nudge-bandwidth model. It also states the Buffer-First Principle: complex choice architecture should be preceded by restoration of resource and decision bandwidth when the target population is depleted. The included simulations are deterministic synthetic demonstrations, not fits to human-subject data. The accompanying replication package contains LaTeX source, Python code, generated figures, CSV outputs, and the synthetic model-comparison table. This draft does not claim to derive λ ≈ 2.25 exactly, reduce all economic behavior to thermodynamics, or replace Prospect Theory. It is a public working draft and timestamped finite-capacity bridge model for future empirical testing.