Generativity Exploitation Propagation: A Conditional Network Model of Cascades and Buffers

Abstract

An actor whose effective generative capability is constrained may face altered opportunities, pressures, and returns when choosing how to continue. One possible response creates a second exploitative relation; cooperation, support, exit, adaptation, and lost practical capacity can yield different outcomes. This position paper develops generativity exploitation propagation as a conditional causal relation between independently evaluated edges. The model requires complete global arrangements, compatible edge-level baselines, a coherent intervention on an upstream mechanism, a separately specified downstream row-satisfaction target, and a material positive total-effect screen. The source-aligned propagation label additionally requires a supported material path through the intermediate actor's capability, viability, or response opportunities. The target remains distinct from its three-valued research audit. Under a finite response-sufficiency restriction, the paper derives a response-kernel identity for the total effect and a sign decomposition in which vulnerability, non-appropriative alternatives, practical capacity, and return can offset one another. A restricted open-cascade approximation yields an expected-generation recursion and a finite subcritical resolvent. Entrywise offspring-kernel reduction yields spectral attenuation under causally comparable regimes, while leaving policy legitimacy and burden displacement open. Countermodels separate propagation from succession, common shocks, absorbed losses, downstream harm, incompatible baselines, and unresolved edge audits. Around this construction the paper develops three further registers. A problem analysis locates the transmitting quantity in subject-level continuation: an actor sustains a trajectory across several generative domains jointly, so a contraction confined to one domain can lower its capacity to continue at all and compel a search for generative conditions elsewhere. The analysis further establishes that edge diagnoses fail to compose, since succession, common causation, and shared mechanisms remain consistent with two positive edge findings, and that the existence of a capability contraction can be accessible while its magnitude remains unidentified. A review locates the proposal among threshold, cascade, systemic-risk, interference, and structural-exploitation traditions, which divide into those modeling transmission without evaluating what is transmitted and those evaluating relations without modeling transmission. A normative argument then answers the question the model raises. Transmitted pressure leaves the intermediate actor's agency intact; the actor's motivating state is preservation of its own continuation rather than opportunism, which makes the conduct both more susceptible to mitigation and more tractable to institutional remedy through the availability of alternatives; and the upstream actor acquires a distinct forward-looking burden, so that responsibility neither migrates upstream nor disappears. A closed-cycle counterexample defeats the inference from reciprocal role occupancy to cancellation and establishes that distributive outcome and relational procedure are independent evaluative registers, from which it follows that stability and subcriticality are dynamical properties carrying no normative verdict. The propagation contrast is proposed as a measure of structural contribution for social-connection accounts of responsibility, which have lacked one. A political-economic register locates coordinating power through value-chain governance types, states the mismatch between the level at which the relations occur and the level at which mediating capacity resides, and argues that existing instruments in this domain regulate observable manifestations in place of couplings, so that an instrument can be fully complied with while the transmission structure operates unchanged. Open questions are collected by register. The construction establishes neither prevalence nor inevitability, assigns no liability, recommends no institution, and classifies no observed relation. It offers a revisable framework for empirical and normative research on open exploitation cascades across AI and non-AI domains.