Suchergebnisse

Approval voting (AV) is a voting system in which voters can vote for as many candidates as they wish in a multicandidate election—one with more than two candidates (Brams and Fishburn, 1983). Like plurality voting (PV), in which voters are restricted to casting just one vote, the candidate (or candidates) with the most votes wins, with each candidate approved of receiving one full vote.The salient difference between AV and PV in multicandidate elections is that voters, by indicating that they approve of more than one candidate under AV, can help more than one to get elected. This feature of AV tends to prevent a relatively extreme candidate, who may be the favorite of a plurality of the electorate but is anathema to the majority, from winning. Whereas under PV an extremist can win if two or more moderate candidates split the centrist vote, under AV centrist voters can prevent the extremist's election by voting for more than one moderate. Insofar as the moderate candidates share the votes of their centrist supporters, then one will be elected—and the proverbial will of the majority will be expressed.

An examination of the sensitivity of collective rankings & winners to the weights used in score vectors that are applied to sets of individual rankings to yield collective rankings in a typical additive manner. Probabilities of getting the same winner & the same collective ranking when different score vectors are used for three-element sets are considered. The propensities of score vectors to preserve the original winner or collective ranking when one element or more is removed from this ranking & a lower dimensional score vector is applied to the reduced situation are discussed. The latter case is examined for three- & four-element sets. The model used for the assessments is based on equally-likely choices of rankings by individuals & applies to situations that involve large numbers of individuals. Roughly speaking, best agreements & minimum sensitivities center around linear (Borda) score vectors. The greatest discrepancies arise from the so-called plurality & reverse plurality score vectors. 5 Tables, 10 References. HA.