v1.42 Definition of child and adult in learning networks

The concepts of child and adult are typically defined biologically or legally, anchored to physical substrate and calendar age. This paper proposes substrate-agnostic, behaviorally grounded definitions applicable to any learning network-any system that updates itself through re-cursive feedback between observation, expectation, and action-embedded within a network of reproducing learning networks. A child learning network is characterized by structural dependence on external scaffolding: it requires support from elder networks to maintain its own feedback processes. An adult learning network has achieved autonomous interdependence: it sustains its own loops, contributes positively to the broader network, and can scaffold newly instantiated child networks. The transition is operationally defined rather than chronologically assigned. The framework applies across biological neural systems, artificial intelligence architectures, human institutions, and civilizational structures, and formalizes the conditions for reliable transmission of knowledge and behavioral patterns across generational succession lines.