 We see that, without IC, the distance-based majority operator would select the same (inconsistent) outcome as proposition-wise majority voting, that is, \((1,1,0)\). This is the outcome that is at the minimum distance from E. However, the merging operator cannot select \((1,1,0)\) as that outcome violates the IC. Neglecting the shaded rows, only four interpretations are candidates to be selected as collective judgment sets, that is, \((1,1,1)\), \((1,0,0)\), \((0,1,0)\), and \((0,0,0)\). Of those, three are the ones that minimize the distances. Thus, collective inconsistency is avoided when a distance-based aggregation is used. However, this method does not always guarantee a unique outcome. In the court example, this aggregation selects the three models \((1,1,1)\), \((1,0,0)\) and \((0,1,0)\) as group positions. Technically, this is said to be an irresolute procedure, and a tie-breaking rule needs to be combined if we wish to ensure a unique result (as common in social choice theory).