Using mathematical tools to ask sharper questions about mind.

Correspondence Matrices and Algebraic Logic give language for logical states and operators. ProLT observation topologies make distinguishability depend on explicitly chosen tests. Binary order thinning studies a narrow, exact structural effect of a new Boolean observation.

Logical Homology and Structured Boolean Factorization explore how logical relationships can be assembled or decomposed. These lines have different scopes and research status.

Evolutionary Logic asks how continuously changing processes acquire discrete logical descriptions. Information and boundaries asks how observations across a system boundary could be modeled. Reflective self-models asks what operational criteria would make a representation genuinely about the system itself.

These pages are research stubs. They state candidate questions and first formal targets so that future work can be evaluated without presenting a conjecture as an established result.

From Observable States to Acquirable Predictive Models connects ProLT's distinctions, RF-IDENT's permitted experiments, and refinement's changing representations to an explicit prediction task. With known deterministic dynamics, it compares the distinctions legal tests can obtain with those needed to predict every future output.

The fixed-state criterion concerns acquiring a predictive label. Once actions change the state during observation, the report uses a separate finite-horizon protocol: certainty about the current state need not identify its origin. This gives a precise instance of the programme's Being-and-Becoming question while leaving learning unknown dynamics, continuous processes, and self-awareness open.