From Mature Ecology to New Hereditary Lineages: Reconstructive Closure and Substrate Transitions develops a comparative framework for identifying where descendant reconstruction actually occurs across biological, ecological, cultural, digital and artificial systems. The paper distinguishes hereditary continuity from reconstruction of the machinery that makes heredity executable. It separates candidate-token lineage fidelity, organisational reconstruction, constitutive implementation and recurrent external reconstructive authorship, combining them through the non-compensatory gate C_{\rm rec}=\min(H_L,J_V^O,J_V^S,R_{\rm old}). The framework was developed across 20 calibration cases and then frozen before application to five pre-specified external stress-test cases. These external cases populated all four closure levels without retrospective modification of the rubric. A notable cross-substrate result is the convergence of the F plasmid and Avida: both preserve strong heredity and candidate-directed organisation while depending on externally reconstructed interpretive machinery. The framework is also applied prospectively to artificial systems. A checkpoint-descended model lineage remains below closure, while a narrow operational software-agent lineage reaches substantial reconstructive closure for a declared controlled multi-hop replication route. Broader AI-development and artificial-industrial ecologies currently fail lineage-candidate admission and are therefore classified as not applicable rather than assigned low closure scores. These results motivate a broader long-cycle hypothesis: mature ecologies can increase candidate-accessible reconstruction opportunities without themselves becoming lineages. New hereditary lineages may emerge within such ecologies as increasing portions of descendant-generating organisation become genealogically internalised. The accompanying supplement includes the frozen v1.0.9 coding manual, freeze declaration, provenance materials and checksums. Independent second-coder reliability analysis remains planned before journal submission. .
Jason Prevett· Zenodo (CERN European Organi...· 0 citations
The Universal Algorithm is a cross-disciplinary popular-science book exploring a recurring pattern in the emergence of higher-order organisation across biological, cultural and computational systems. The central proposal is that adaptive units can sometimes build a more capable level of organisation above themselves when the benefits of shared information, memory and control exceed the costs of coordination, and when the resulting architecture becomes sufficiently closed to persist as a selectable unit. The book follows this process from early life and multicellularity through nervous systems, language, writing, institutions, the internet and artificial intelligence. Rather than treating complexity as an inevitable upward march, the framework describes a conditional transition sequence. Successful lower-level units communicate; communication creates coordination burdens; persistent external scaffolds extend memory and control; selective enclosure protects useful organisation; energetic, informational, viability and lineage closure determine whether the new structure can maintain itself; and, in sufficiently mature cases, causal control may shift from the lower-level units toward the higher-order organisation. Once established, that higher-level organisation can itself become part of a new population in which the same problem begins again. A recurring theme is the Freedom-Security Exchange: lower-level units may surrender some autonomy or duplicated capability in exchange for greater security, specialisation, efficiency or collective reach. The book also distinguishes higher-level agency from consciousness. Agency is treated operationally as the capacity of a system to sense, integrate information, retain state, select actions and causally influence its own future viability. The framework is presented as a scientific hypothesis rather than a completed theory. It explicitly allows for stalled transitions, simplification, fragmentation and collapse. The final sections set out testable predictions, falsification criteria and the conditions under which the proposed pattern should fail. Particular attention is given to artificial intelligence, where the book argues that the digital substrate is currently more than passive infrastructure but less than a fully closed new evolutionary individual. Whether such a transition completes is treated as an empirical question. The narrative is written for a general audience and uses historical examples, reconstructed scenes, diagrams and the author’s experience as a bricklayer to make the underlying mechanisms intuitive without requiring mathematics. A technical companion manuscript, From Communication to Higher-Level Agency: Selective Enclosure, External Scaffolding, and Recursive Substrate Transitions in Adaptive Systems, develops the core mechanism mathematically and includes a proof-of-concept multi-agent simulation. The book is intended as the broader conceptual and narrative presentation of that research programme. First Open Edition, Version 1.0.
Jason Prevett· Zenodo (CERN European Organi...· 0 citations
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