QORA v0.3 Core Engine: Quantum-Formal Observation-Resistance Algorithm, Python Implementation and Technical Appendix

QORA v0.3 Core Engine is a quantum-formal, classical data-science implementation scaffold for the Quantum Observation-Resistance Algorithm (QORA). The package contains the QORA v0.3 working paper, a technical appendix, and an executable Python core engine.

QORA models observer-relative legibility, basis-dependent classification, transformation-invariance, Phi-gate bias, eigen-spin fidelity, and phenomenon-gate / connection-amplitude effects. The framework does not claim that persons, institutions, archives, or cultural formations are physically quantum systems. Instead, it uses quantum-formal and isomorphic language to represent how projections, transformations, observer-method bases, and evaluability gates shape what becomes legible.

The Python implementation maps QORA concepts into classical numerical structures: projection states as normalized embedding vectors, transformations as linear operators or semantic perturbations, eigen-spin fidelity as squared vector overlap, Phi-gate bias as total variation distance between class distributions, and phenomenon-gate effects as observer-relative connection amplitude.

This release is intended as an experimental research scaffold, conceptual prototype, and reference implementation for studying basis-dependent legibility, predictive profiling, institutional measurement, and observer-relative phenomenality.