New SW method: Weighting with elimination & renormalization
seppley at alumni.caltech.edu
Tue Apr 23 01:21:25 PDT 1996
The following method was proposed by Mike York, a subscriber of a
maillist which is focussed on developing online voting software.
Mike York claimed it doesn't have the lesser-of-evils dilemma and
isn't subject to tactical manipulation. I suspect he's wrong on
both claims, but present his method here anyway.
Each voter rates each candidate using any whole number (0 to N)
that the voter wishes.
Mike York didn't specify this, but it's probably a good idea to
treat unrated candidates as if they were rated 0.
While there is more than one candidate remaining
Normalize each ballot by dividing each voter's ratings by the
maximum rating on his/her ballot.
For each candidate, sum his/her/its normalized ratings.
Eliminate the candidate with the smallest sum, and eliminate
from each ballot the voter's rating of this candidate.
Note that the normalization step is inside the while loop. If an
eliminated candidate was the top-rated candidate on some ballot,
then that ballot's other ratings will renormalize so the second-
from-the-top gets a full-strength vote.
The first time this ballot is normalized, each rating is divided by
500 and it becomes
Suppose Nader is the first candidate eliminated. Then this ballot
and is renormalized (by dividing each rating by 2) to:
So in this scenario where Nader is eliminated first, the ballot
becomes a full-strength vote for Clinton over Dole.
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