Independent public-benefit research
MOLETARIAT
CognitionMathematical physicsShared evidence + governance
Build the distinction. Keep the trail.
Moletariat develops small, inspectable research systems for learning and physical theory. Arina and Relational Physics share machinery and lessons, but they are separate projects with separate claims.
Working ruleBe less wrong on the next loop. Make it buttery smooth. If you build it twice, build it once.
Current portfolio
Two projects. One shared discipline.
Each programme keeps its own evidence boundary, targets, and reading path.
- 01Cognition and learner researchActive · bounded results
Arina
A developmental, domain-neutral learner exploring how distinctions become models, language, memory, self-repair, and reusable methods under external authority.
Explore Arina → - 02Mathematical physics researchActive paper stream
Relational Physics
A separate programme building a graph of mathematical distinctions and testing it through Yang–Mills, finite transport, C-worlds, tomography, and subsequent papers.
Explore Relational Physics →
Shared method
One workshop, without one blurred claim.
The projects cross-pollinate through graph structure, finite evidence, and compositional methods. Their conclusions do not transfer automatically. Each result must still earn its own route through the relevant project.
- DISTBuild distinctions
Treat understanding as a structure that can grow, compose, and expose what is still missing.
- FAILRetain failures
A wrong route is useful negative space when it remains available to test the next repair against.
- EVIDKeep the route inspectable
Targets, papers, publication stages, and their supporting records remain linked rather than becoming detached claims.