Forwarding was a single global ForwardProb; make it a per-student
composite (Config.ForwardChance): baseline propensity raised by the
fake's Novelty, lowered by ambient HarmAwareness, and scaled down for an
educated student by ProgramEffect (1 = today's hard block). RunCascade
now takes a precomputed per-student []float64 chance and has no education
special case. Defaults are behaviour-neutral, so the 82/58/6 golden
tests are unchanged; the model is tuned in a later slice.
One random threshold per DIRECTED edge, drawn once per world: scenarios
sharing thresholds differ only in who is educated, the prototype's
'same world, different lever' trick. The cascade is plain BFS in rounds;
an educated student receives the fake but never forwards it, which is
the entire effect of the lever. The result stores the first-reached
round per node (exactly what a frontend animation needs).
Tests hand-craft a 4-node line graph with exact thresholds, so every
expectation is exact: spread, directional blocking, educated cutoff.
