[email protected] wrote:
How did this thread get side tracked to Proportional Representation?
Proportional Representation only works for multi-winner elections.
Of course, everybody knows that PR is the way to go in multi-winner elections.
And why is that? Because it solves the tyranny of the majority problem in that
setting.
So why cannot we see that this same problem exists in single winner elections? I
suggest that the analogous remedy in the single winner setting is proportional
probability. The simplest method that accomplishes this is random ballot. But,
as I suggested, there are better stochastic methods that yield probability
distributions with less entropy while still solving the tyranny of the majority
problem..
An assembly picked by PR stabilizes itself because the differently
positioned candidates balance each other out and actually meet and
discuss. If the assembly rules have supermajority rules, that may also
make it more likely to reach a consensus rather than oscillating between
extreme positions.
On the other hand, in a single-winner election, there is only one
winner. That winner usually won't have an "inner assembly" to balance
himself. Thus, I think that the reaction against nondeterministic
methods arise from the thought that if we can't be sure who will win,
the candidate who wins might win simply by the luck of the draw and be
unsuitable - and then we're stuck with him without other council members
to moderate him.
Abd's 10% example is an example of this. If 10% think [disastrous
policy] is really good and votes accordingly, then by using Random
Ballot, you'd get that disastrous policy 10% of the time. While Random
Ballot may find a brilliant policy that only 10% knows of, it can't
discern between that and a horrible policy that (rightly) no more than
10% support, and the loss from the latter would more than outweigh the
gain from the former.
Or so one would argue.
In a low-entropy method, as far as I understand it, there still has to
be a random component that encourages the voters to find a compromise.
If the fallback component is too close to a deterministic method, then
the majority won't care to try and find a consensus because they'll
benefit more from the fallback. On the other hand, if it's too random,
it could be bad indeed if the different groups truly can't find a
compromise.
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