Warren Smith wrote:
So perhaps the best or simplest way to resolve the inherent conflict
(in multiwinner voting systems) between the two goals of (a) good
representation and (b) good winner quality, is... to accept it.
Let the Hybrid Bayesian Regret of a multiwinner voting system be a
LINEAR COMBINATION of 1-stage and 2-stage regret. Call the weights W1
and W2.
You could also simply plot the results in 2D, setting the x coordinate
to be 1-stage and y coordinate to be 2-stage. That would be similar to
my proportionality-regret diagrams. You could then find the Pareto front
and let whoever may desire to do so, draw a curve or a line on it to
find the optimum according to whatever combination they want.
2-stage BR is explained here:
http://www.rangevoting.org/BRmulti.html
A note on this: I also think there's a checks-and-balances dynamic
within the parliament and between the parliament and the voters. In the
former, members of different parties (or members of the same party, if
elected by party-neutral methods) keep each other from veering off
towards corruption; in the latter, the voters can see, by the actual
bargaining being done in parliament, whether some representatives are
acting against their wishes, and if so, which representatives are. These
effects would not, I think, be reflected by 2-stage BR. A more
sophisticated 2-stage BR might use game theory to try to account for
such things, but exactly how, I'm not sure.
1-stage regret is simply the sum (over all voters and all winners) of
utilities for the winners for the voters -- subtracted from same thing
with the optimum winners who would have maximized this 1-stage utility
(this subtraction makes it a "regret" rather than a "utility").
You may object "the weights in this linear combination are arbitrary!"
That's a valid objection. However, I could counter that maybe that is
the way things really are. This is just yet another "knob" on the
side of the "Bayesian Regret machine" -- others include #candidates,
#winners, utility-generation model, voter-behavior model, etc.
All your other knobs are input knobs, no? The #candidates, #winners,
utility generation models and parameters, etc., specify what kind of
data is run through the voting methods (and subsequent utility
determination function), whereas the weight-knob is an adjustment of the
(combined) utility function itself.
So it would seem to be a quite different sort of knob. Adjusting it
would be similar to adjusting 1-stage BR between, say, mean utility and
worst utility (maximin).
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