Everything about Minimax Condorcet totally explained
Minimax is often considered to be the simplest of the
Condorcet methods. It is also known as the
Simpson-Kramer method, and the
successive reversal method.
Minimax selects the candidate for whom the greatest
pairwise score for another candidate against him is the least such score among all candidates.
When it's permitted to rank candidates equally, or to not rank all the candidates, three interpretations of the rule are possible. When voters must rank all the candidates, all three rules are equivalent.
The score for candidate
x against
y can be defined as:
- The number of voters ranking x above y, but only when this score exceeds the number of voters ranking y above x. If not, then the score for x against y is zero. This is sometimes called winning votes.
- The number of voters ranking x above y minus the number of voters ranking y above x. This is called using margins.
- The number of voters ranking x above y, regardless of whether more voters rank x above y or vice versa. This interpretation is sometimes called pairwise opposition.
When one of the first two interpretations is used, the method can be restated as: "Disregard the weakest
pairwise defeat until one candidate is unbeaten." An "unbeaten" candidate possesses a maximum score against him which is zero or negative.
Minimax using
winning votes or
margins satisfies
Condorcet and the
majority criterion, but not the
Smith criterion,
mutual majority criterion,
independence of clones criterion, or
Condorcet loser criterion. When
winning votes is used, Minimax also satisfies the
Plurality criterion.
When the
pairwise opposition interpretation is used, minimax also doesn't satisfy the
Condorcet criterion. However, when equal-ranking is permitted, there's never an incentive to put one's first-choice candidate below another one on one's ranking. It also satisfies the
Later-no-harm criterion, which means that by listing additional, lower preferences in one's ranking, one can't cause a preferred candidate to lose.
Further Information
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