Rear-View Epistemology and the Paradox of Evolutionary Endpoints
Abstract
Human scientific knowledge is necessarily participant-bound and retrospective: theories are constructed from observationally accessible realized events through instruments, conceptual frameworks, and reference models that themselves accumulate and evolve. This paper develops this limitation as Rear-View Epistemology and examines what it permits an embedded observer to infer about completed reality. A central distinction is drawn among realization, discovery, and prediction. Already-realized structure may remain undiscovered and may later be recovered out of historical sequence, whereas predictive science operates prospectively across an observational boundary, from presently accessible conditions toward outcomes not yet available for confirmation. Predictive success therefore establishes the reliability of an asymmetric relation; it does not establish that the predicted outcome was already actual before observation. This distinction becomes decisive for the strong 4D block universe completion claim that every physical event has already happened. The paper does not conclude that a 4D manifold is self-refuting, nor that ordered causal, thermodynamic, or evolutionary structure cannot be represented in such a manifold. It concludes that participant observation and predictive success do not warrant the further claim that the entire future — including the observer’s own later observations and revisions — is already actual. Tenseless existence is treated as a different predicate, not as a repair of the same claim. Dual-Layered Reality is introduced only at the end, as one architecture that keeps a complete lattice of potential distinct from sequential realization. The argument concerns not the legitimacy of predictive science, but the promotion of participant-level predictive models into author-level claims about completed actuality.
Fields of Study & Subjects
Philosophy and History of Science
Philosophy and Theoretical Science
Embodied and Extended Cognition
Publication details
- Publication date
- 2 April 2026
- Document type
- Preprint