[EM] How to make a summable version of STV

[fsimmons at pcc.edu]

Kristopfer.

Look at it this way, the process of amalgamating the factions is a low pass filter that gets rid of some fo 
the noise.  So why not consider the resulting ballots as the "true" ballots, and the associated weights 
tell how many of them there are of each kinsd.  STV can be done with these new true ballots, Droop 
quotas and all.

----- Original Message -----
From: Kristofer Munsterhjelm 
Date: Saturday, July 23, 2011 1:53 am
Subject: Re: [EM] How to make a summable version of STV
To: fsimmons at pcc.edu
Cc: election-methods at lists.electorama.com

> fsimmons at pcc.edu wrote:
> > This is to illustrate a point that Warren has recorded on his 
> website> somewhere (I don't remember exactly where); namely that 
> lack of
> > summability is not insurmountable.
> > 
> > We start with the assumption that the voters have range style 
> ballots> on a scale of zero to six. [Seven levels are about 
> optimal according
> > to the psychometrics experts.]
> 
> I thought five was, not seven. Do you have any papers?
> 
> > At each precinct the ballots are sorted into n piles, one for each
> > candidate. The ballots in each pile are averaged together to 
> get a
> > rating vector for each candidate. [At this first stage if a
> > candidate shares (with k-1 other candiates) top rating on a ballot,
> > then a copy of that ballot is sent to each of those candidate's
> > piles, along with a weight of 1/k .]
> > 
> > The precincts send the n candidate vectors, together with their
> > respective totalweights to the counting center. For each 
> candidate a
> > weighted average of the vectors for that candidate from all of the
> > precincts is computed, and the total weight is taken as the 
> size of
> > that candidate's faction.
> > 
> > The STV computation is then based on these n almagamated factions.
> 
> That would fail the Droop proportionality criterion. Just take 
> your 
> favorite example where Range fails it, then stick an universal 
> favorite 
> candidate X in front of every voter's vote. Now, there's only 
> one rating 
> vector - X's - and the averaging will smooth out any structure 
> beyond X.
> 
> This is an extreme example, but the averaging could hide detail 
> in more 
> realistic ballot sets, too.
> 
>