It seems to me these outliers could be balanced across national districts given 
access to tax returns.
It’s a bin packing problem.

From: Friam <friam-boun...@redfish.com> on behalf of Tom Johnson 
<t...@jtjohnson.com>
Reply-To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
Date: Sunday, November 4, 2018 at 11:48 AM
To: "Friam@redfish. com" <friam@redfish.com>
Subject: Re: [FRIAM] gerrymandering algorithm question

Because doing such classifications would be far too difficult.  For example, we 
know some very, very rich people - - private-jet rich - - in Santa Fe who are 
extremely liberal in their politics and generous to liberal causes and 
politicians.
TJ

On Sun, Nov 4, 2018, 10:54 AM Marcus Daniels 
<mar...@snoutfarm.com<mailto:mar...@snoutfarm.com> wrote:
Why not put aside geography?   For every democratic UC professor in Berkeley, 
draw a republican fracking executive from North Dakota.
Now we have airplanes and the internet.   All these tribes are causing a lot of 
problems.   Time to break them up.

From: Friam <friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>> on 
behalf of Nick Thompson 
<nickthomp...@earthlink.net<mailto:nickthomp...@earthlink.net>>
Reply-To: The Friday Morning Applied Complexity Coffee Group 
<friam@redfish.com<mailto:friam@redfish.com>>
Date: Sunday, November 4, 2018 at 10:24 AM
To: 'The Friday Morning Applied Complexity Coffee Group' 
<friam@redfish.com<mailto:friam@redfish.com>>
Subject: Re: [FRIAM] gerrymandering algorithm question

Forgive me, but I am too old and dumb to do nodes and edges talk.  Could 
somebody translate this into  defrocked Harvard English major talk.  What value 
is maximized by such a system?

Nick

Nicholas S. Thompson
Emeritus Professor of Psychology and Biology
Clark University
http://home.earthlink.net/~nickthompson/naturaldesigns/

From: Friam 
[mailto:friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>] On Behalf 
Of Marcus Daniels
Sent: Saturday, November 03, 2018 10:14 PM
To: The Friday Morning Applied Complexity Coffee Group 
<friam@redfish.com<mailto:friam@redfish.com>>
Subject: Re: [FRIAM] gerrymandering algorithm question

Consider a network where the nodes represent individual membership in a 
district and the edges connect any two individuals that could possibly be 
considered as being in the same area.   An edge has a weight of -1 if the 
neighbors are in opposing political parties and 1 if they are the same.   A 
node has the value of 1 if it is in a district and -1 if it is not in that 
district.    Districts are mutually exclusive, so all of the nodes associated 
with an individual, when considered as binary values, must sum to one.  
Specifically suppose there are two districts, and node(A,D) is defined as 
individual’s A participation in district D.  Then 
(node(A,0)+1)/2+(node(A,1)+1)/2 = 1.   Constraints like this can be converted 
into penalties by moving the RHS to the LHS, negating the value, and then 
squaring the LHS.  An energy for the whole network can be written as a sum of 
all of the network’s interactions.

    sum(edge_weight(i,j)*node(i,d)*node(j,d)) where i < j for i,j from the set 
of nodes and d from the set of districts
     + K*(all mutual-exclusion penalties as above) where K is a large number

Now minimize this energy using a system that can find the ground states of a 
high dimensional Ising model, such as a quantum annealer.  This function will 
be minimal when each district has neighbors that tend to be in different 
parties.

From: Friam <friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>> on 
behalf of Tom Johnson <t...@jtjohnson.com<mailto:t...@jtjohnson.com>>
Reply-To: The Friday Morning Applied Complexity Coffee Group 
<friam@redfish.com<mailto:friam@redfish.com>>
Date: Saturday, November 3, 2018 at 4:55 PM
To: "Friam@redfish. com<mailto:Friam@redfish.%20com>" 
<friam@redfish.com<mailto:friam@redfish.com>>
Subject: Re: [FRIAM] gerrymandering algorithm question

First, we would have to agree on whether there will be objectives related to 
the demography of any district?  I prefer only counting the number of current 
population 18 and over.  Or some would argue for the total population of any 
age.  But given either choice, there will be serious suggestions that doing so 
would work hardship on racial, ethnic or other groups.  Could be, but it could 
also mean that anyone running for office would probably have to find a way to 
appeal to ALL voters.

Second, let's say we're creating Congressional districts.  Overlay a state with 
a grid of hexagons of X diameter; could be 100 yards or 1000.  I don't know, 
but perhaps something like Netlogo could give us a scalable system to run tests.

Third, given a known population of potential voters, we know how many 
Congressional districts a state would have.  Randomly distribute that number of 
hexagons across the state with the objective of maximizing the centroid 
distances of all the hexagons.

Fourth, expand out from each hexagon one additional hexagon at a time in a 
circular fashion with all expansions starting on the same side of the original 
hexagon.  Total the number of potential voters.  If there are no potential 
voters in a hexagon, advance one more in the rotation.  Then repeat the same 
expansion, total the voters and do it again until the desired district 
population is reached.

There are obvious problems here: e.g. what happens when a district encounters a 
state boundary or another district's hexagon early on?  I don't have a solution 
(yet).  But I think this simulation could be easily tested without a lot of CPU 
overhead.  And after the districts are created, we could start to look at the 
demographics of the potential voters.

TJ

============================================
Tom Johnson
Institute for Analytic Journalism   --     Santa Fe, NM USA
505.577.6482(c)                                    505.473.9646(h)
NM Foundation for Open Government<http://nmfog.org>
Check out It's The People's 
Data<https://www.facebook.com/pages/Its-The-Peoples-Data/1599854626919671>
http://www.jtjohnson.com<http://www.jtjohnson.com/>                   
t...@jtjohnson.com<mailto:t...@jtjohnson.com>
============================================


On Sat, Nov 3, 2018 at 4:14 PM Nick Thompson 
<nickthomp...@earthlink.net<mailto:nickthomp...@earthlink.net>> wrote:
Oh, I absolutely agree that we could design districts to maximize any variable 
we wanted.  And with a little luck, we might maximize a couple, or even three.  
But inevitably, we will encounter some variable that is negatively correlated 
with those we already maximize, so even we philosopher kings will be 
dissatisfied with the result.

So, you philosopher-kings out there:  if you were designing districts out 
there, how would you do it.  How about all districts at-large?  Ranked choice 
voting?  How about requiring all districts to match the state-wide political 
distribution of the whole state and redistricting after every election?  
Seriously.  How would you do it?

Nick

Nicholas S. Thompson
Emeritus Professor of Psychology and Biology
Clark University
http://home.earthlink.net/~nickthompson/naturaldesigns/

From: Friam 
[mailto:friam-boun...@redfish.com<mailto:friam-boun...@redfish.com>] On Behalf 
Of Marcus Daniels
Sent: Saturday, November 03, 2018 11:24 AM
To: The Friday Morning Applied Complexity Coffee Group 
<friam@redfish.com<mailto:friam@redfish.com>>
Subject: Re: [FRIAM] gerrymandering algorithm question

Nick writes:

“I don’t mean to say that “fair districts” aren’t possible.  I just mean to say 
that I, as your philosopher-king, could not design them.”

Wasn’t there a recent effort by the MIT Sloan school to redesign the school bus 
routes in Boston?   They managed to reduce the cost and time of the routes by a 
large amount, but then many complained because it didn’t reflect the underlying 
class structure of the community and the preferences of the richer communities.

One can design an optimization to balance any set of goals.  It’s just that 
some of the goals we don’t talk about.  They are wired-in to our reptile brain 
as baseline expectations and not reflected in the political conversations of 
dinner parties.

Marcus
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