This repository implements a deterministic exclusion engine where governance decisions are treated as a mechanical process rather than a probabilistic one. Candidates exist as stateful objects that accumulate strain under a scheduled constraint pressure. Pressure is applied across explicit phases—nucleation, quenching, and crystallization—and exclusion occurs only when accumulated stress exceeds a fixed yield threshold. Once fractured, a candidate cannot re-enter; history matters.
There is no ranking, sampling, or temperature. Given identical inputs, configuration, and substrate, the system always produces bit-identical outputs, verified by repeated hash checks. The implementation explores different elastic modulus formulations that change how alignment and proximity contribute to stress, without changing the deterministic nature of the process. The intent is to examine what governance looks like when exclusion is causal, replayable, and mechanically explainable rather than statistical. Repository: https://github.com/Rymley/Deterministic-Governance-Mechanism
OK, this is AI slop ("fracture" alone gives it away). But maybe there's still something of value here? Can you explain it in actual human terms, give a real example, and explain what you did to test this and why I shouldn't flag this like I did https://news.ycombinator.com/item?id=46701114 ?
I don't even understand what discipline we're talking about here. Can someone provide some background please?