[FRIAM] gerrymandering algorithm question

Sun Nov 4 14:20:41 EST 2018

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-bounces at redfish.com> on behalf of Tom Johnson <tom at jtjohnson.com>
Reply-To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com>
Date: Sunday, November 4, 2018 at 11:48 AM
To: "Friam at redfish. com" <friam at 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 <marcus at snoutfarm.com<mailto:marcus at 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-bounces at redfish.com<mailto:friam-bounces at redfish.com>> on behalf of Nick Thompson <nickthompson at earthlink.net<mailto:nickthompson at earthlink.net>>
Reply-To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com<mailto:friam at redfish.com>>
Date: Sunday, November 4, 2018 at 10:24 AM
To: 'The Friday Morning Applied Complexity Coffee Group' <friam at redfish.com<mailto:friam at 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-bounces at redfish.com<mailto:friam-bounces at redfish.com>] On Behalf Of Marcus Daniels
Sent: Saturday, November 03, 2018 10:14 PM
To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com<mailto:friam at 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-bounces at redfish.com<mailto:friam-bounces at redfish.com>> on behalf of Tom Johnson <tom at jtjohnson.com<mailto:tom at jtjohnson.com>>
Reply-To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com<mailto:friam at redfish.com>>
Date: Saturday, November 3, 2018 at 4:55 PM
To: "Friam at redfish. com<mailto:Friam at redfish.%20com>" <friam at redfish.com<mailto:friam at 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/>                   tom at jtjohnson.com<mailto:tom at jtjohnson.com>
============================================

On Sat, Nov 3, 2018 at 4:14 PM Nick Thompson <nickthompson at earthlink.net<mailto:nickthompson at 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-bounces at redfish.com<mailto:friam-bounces at redfish.com>] On Behalf Of Marcus Daniels
Sent: Saturday, November 03, 2018 11:24 AM
To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com<mailto:friam at 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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