[FRIAM] gerrymandering algorithm question

Tom Johnson tom at jtjohnson.com
Sun Nov 4 13:48:12 EST 2018


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 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> on behalf of Nick Thompson <
> nickthompson at earthlink.net>
> *Reply-To: *The Friday Morning Applied Complexity Coffee Group <
> 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>
> *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] *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>
> *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> on behalf of Tom Johnson <
> tom at jtjohnson.com>
> *Reply-To: *The Friday Morning Applied Complexity Coffee Group <
> friam at redfish.com>
> *Date: *Saturday, November 3, 2018 at 4:55 PM
> *To: *"Friam at redfish. com" <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                   tom at jtjohnson.com
> ============================================
>
>
>
>
>
> On Sat, Nov 3, 2018 at 4:14 PM Nick Thompson <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] *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>
> *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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