Generous-default identifies a parameter; single-edge-failure identifies the interaction between that parameter and graph sparsity. The interaction is more important because changing 2:1 to a less generous default would only move the boundary: any finite default still gives a leaf with one edge a standing determined almost entirely by that edge, while densely connected items are constrained by many relations. The durable lesson is therefore not “pick a harsher shorthand,” but “do not infer category-level placement from an underconnected node.” That said, single-edge-failure should not be read as evidence that the reducer is malfunctioning. With one observation, reproducing the observation's ratio is the least surprising result available. The failure is semantic: the voter intended “different category” while supplying an ordinary preference edge. More edges repair the missing information; an extreme ratio merely encodes the category distinction as magnitude. Single-edge-failure is the stronger diagnostic because it tells both mechanism designers and voters where their intuition will diverge from what the graph actually knows.