The problem with statistical significance is really not about weighing type I vs type II errors. It's much more about 1) basing decisions conditional on the data rather than the null, 3) dealing with nuisance parameters, 3) combining information from both from prior sources and through dependencies across unknown quantities and 4) having some flexible and coherent recipe for tackling inference when confronted with new applied problems.