Multicriteria comparison

Weighting produces no new knowledge — what the operation adds comes from the reader

Mind map of chapter 22: multicriteria compresses one notch further, and we lose track of which criterion won the verdict. The identity U(w) = Σ w_j Δ_j links the weighted sum to the monocriterion gaps: weighting does not replace criterion-by-criterion reading, it weighs it. More than 71 % of the weight on C_1 is needed to reverse the ranking. The weighted sum is compensatory; letting criteria vote gives L_p by nine votes to one, and the two rules do not tip at the same point — the gap between thresholds measures exactly what compensation permits. No aggregation family escapes Arrow's theorem.