Evolutionary Relativity: Frame-Qualified Organizational Change and Observer-Relative Reconstruction

In this paper, evolutionary refers to organizational change along the temporally extended history of an adaptive system, not to Darwinian change across generations. Evolutionary Relativity studies a relation: an observed system traverses an organizational path, while another adaptive organization reconstructs that path through finite evidence, reference states, temporal coverage, resolution, and comparison capacity. The central distinction is between path and endpoint: matched start and end states can conceal different amounts of established intermediate change. The paper separates a protected registered measurement frame from the frame of the studied observer and reports a finite registered-refinement path estimate rather than claiming an infinite-resolution curve length. The canonical target is an independently motivated continual learner operating in a partially observable, non-stationary task stream. Its loss, update rule, and environment are fixed before path and rival summaries are selected. Candidate histories arise from real adaptive runs under pre-registered curricula, drift schedules, data orders, replay budgets, and random seeds; the trajectory bank is screened from that pool rather than synthesized to prescribed summary values. A history-dependence gate requires a history-aware predictor to outperform a current-only predictor, and a non-designed-sufficiency gate prohibits embedding path or rival summaries in the target dynamics. The studied observer predicts the target's next response given the next external input, receives no path supervision, and is frozen before probing. Raw-channel calibration tests both extractability and probe fairness; frozen-representation results are normalized against each summary's raw-channel recoverability. The target characteristic timescale τ(Pᴹ) is estimated from amplitude-weighted temporal correlation and must be empirically separable from persistence, transition count, recency, and path. ER's empirical wagers are whether path survives in the frozen observer representation better than identifiable rivals, whether defined degradations produce the registered residual-proxy shift, and whether the readable-scale optimum moves jointly with observer capacity and the independent target timescale. This is a pre-validation theoretical status, not empirical support. This manuscript is a preprint and has not undergone peer review.