Aggregation of value judgements differs from aggregation of preferences

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ABSTRACT: This paper focuses on the contrast between aggregation of individual preference rankings to a collective preference ranking and aggregation of individual value judgments to a collective value judgment. The targeted case is one in which the two aggregation scenarios exhibit a far-reaching structural similarity: more precisely, the case in which the individual judgments that are to be aggregated are value rankings. This means that, formally, the individual judgments are isomorphic with individual preference rankings over a given set of alternatives. The paper suggests that, despite their formal similarity as rankings, the difference in the nature of individual inputs in two aggregation scenarios has important implications: the kind of procedure that looks fine for aggregation of judgments turns out to be inappropriate for aggregation of preferences. The relevant procedure consists in similarity maximization, or – more precisely – in minimization of average distance from individual inputs. It is shown that, whatever measure is chosen, distance-based procedures violate the (strong) Pareto condition. This seems alright as value judgment aggregation goes, but would be unacceptable for preference aggregation, on the most natural interpretation of the latter task.

When applied to judgment aggregation, distance-based procedures might also be approached from the epistemic perspective: questions might be posed concerning their advantages as truth-trackers. From that perspective, what matters is not only the probability of the outcome being true, but also its expected verisimilitude: its expected distance from truth.