Using Urban County Clusters To Guide Redistricting

[muon2]

Yes, good example. The case is rare enough, that I suppose for those two examples, one could choose to have a unique pre-agreed upon exception, or not. The loser of the neutral county competition might prefer such an exception potentially.

I am not sure what you meant, or whether you meant a distinction, between take the rule or have a scoring penalty? If you take the rule, you just cannot have an extra chop at all?

Yes that's what I mean. A mapping rule is something that cannot be avoided. A scoring rule creates a cost for the extra chop, but permits flexibility. The downside of flexibility is that plans like my MI plan that splits Lansing may get through for commission review and might even bump out a more appealing plan. Also every flexible rule can potentially open the door to those who want to game the system. A hard rule cuts plans like that off at the start, but will also cut out some plans like the 4-split of the Cincy cluster or the separation of Summit from Portage.

[Torie]

Man you have bought into this urban cluster thing lock, stock and barrel haven't you? A veritable epiphany, with Jimtex your mentor. I can't say that I disagree with the hard rule however, but can't really sign off until enough examples are explored. Did I ever tell you that I loved the common law? It is all those examples, that allow lesser minds like myself to really get it around an idea, and have adequate perspicacity to fathom all of its significant consequences. I in short need mental crutches.  So be patient with those of us relatively mentally handicapped "challenged." As I say in so many economic contexts, time horizons matter!

[traininthedistance]

Some CD had to take the balance of Stark after the Akron CD going down to take the city of Canton and stuff in between had its fill of population. The idea was to keep Akron and Canton together, with a nice compact result as well. But all of that assumed that Akron/Canton was a metro area of some sort, and who knew Summit and Portage were?  Summit grabbed the wrong county! So of course, with the new urban cluster definition, in that respect my map is blown out in NE Ohio. You change the rules, and you play the game differently. Akron goes to Kent State, and not to Canton. Who knew?

As to Dayton, what you are just saying is that there can be but one chop into the Cincy cluster, so take your best shot. Fine. I understand that. If you chop Clermont, you can't chop Warren too. The problem however is that the Cincy and Dayton clusters are just wrong. That is because of the whole county, rather than split county syndrome. If one cluster takes part of a county, and another cluster the part on the other end, then the county should be chopped for purposes of defining the perimeters of an urban cluster, rather than just awarding the whole county to the cluster that has a higher percentage of the county population within it, or whatever the rule is. So the issue is whether to made an exception for this one rifle shot issue - correcting for perimeter drift effected for the winner of the split county which has how most population therein game.

I am trying to think of another county in the US that has this issue. I am sure that there are; I just can't put my finger on any at the moment. It's rare to have two separate substantial cities merge towards one another in a neutral county in-between them. It would apply to Dallas and Ft Worth perhaps, except that there is no neutral county between them.

I expect that Mercer County, NJ would qualify as well, being the merger point between the New York and Philadelphia areas.  Except, of course, that the urbanized area kind of does actually merge by now- we are getting to the point where a "New York-Philadelphia CSA" might technically be correct, as ridiculous as that sounds.

In any case, New Jersey is a state where you just can't go by counties for most districts (since it is all so urban and there are twelve districts for twenty-one counties), but you can try and keep the far northwest and far south counties whole at least, and not be gratuitous in the actual urban areas, and also have Mercer be the "flex point" that gets chopped between Philly-area districts and NYC-area districts.

[traininthedistance]

This of course raises the question of what to do in larger conurbations where the "urbanized area" is artificially chopped at a county line, when in all actuality it is one continuous band, but is just given a different label when it passes from MSA to MSA.  I am pretty sure this is what happens at the Summit-Stark border, no?  I know it was mentioned as happening between Baltimore and Harford in MD in some other thread, which surprised me greatly.

[muon2]

Man you have bought into this urban cluster thing lock, stock and barrel haven't you? A veritable epiphany, with Jimtex your mentor. I can't say that I disagree with the hard rule however, but can't really sign off until enough examples are explored. Did I ever tell you that I loved the common law? It is all those examples, that allow lesser minds like myself to really get it around an idea, and have adequate perspicacity to fathom all of its significant consequences. I in short need mental crutches.  So be patient with those of us relatively mentally handicapped "challenged." As I say in so many economic contexts, time horizons matter!

So perhaps we should look at MN since it is has adjacent clusters with an overlapping urbanized area. That may tell us if there are problems with the rule. The clusters are
Minneapolis (Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, Sherburne, Washington, Wright) - 4.620
St Cloud (Benton, Stearns) - 0.285
Mankato (Blue Earth, Nicollet) - 0.146

With a hard rule the Mpls cluster counties cannot be covered by more than 5 CDs. St Cloud can be added to that since the total is still within 5, or it can go in its own CD separate from Mpls. Perhaps you want to pull up one of your old maps to revisit as I will mine?

[jimrtex]

As I noted, the 5% is acceptable only for legislative districts when there is no stricter state standards. jimrtex favors a more relaxed standard for apportionment regions, but that is ineffective at reducing regular chops. For CDs the range can be up to 1% if the state can show consistently applied principles, and there is no smaller range using those same principles. A 0.5% deviation is an easy way to insure a range within 1%.

You're reading Tennant as narrowly as Karcher had been read.

Good faith effort can not be so narrowly defined as:

GOOD_FAITH = 0.005.

While avoiding a mini-chop which would have moved 15,000 persons.   You sliced between Portage and Summit.  You did not make a good faith effort to preserve that urban county cluster.

And range criteria is the wrong one to apply.  If you'd like, I'll show the MALC proposal for Texas House seats that cranked every Republican/Anglo seat up to 4.99%.  If the redistricting application displayed another digit, they would have gone to 4.999%.  Good faith is attempting to hit the bulls eye, and scoring 10 if you are within or even touching the ring.  Bad faith is to carry the red arrows down to the target, and insert them so that they are touching the ring.

I don't find any comfort in Tennant that a 5% variation would be permitted in congressional districts. The opinion said that a range of 0.79% was considered a minor deviation under Karcher and is still minor today, despite the ability of computers to create plans with less deviation. Since it is a minor deviation the state needed to show that the deviation was necessary to meet legitimate state objectives, not merely a good faith effort to meet those objectives. A 5% deviation for congressional districts has not been seen as minor to SCOTUS in the past, and there is nothing in the opinion to suggest that would change. I also reiterate that SCOTUS has consistently used population range, not percent deviation, to measure inequality between the largest and smallest district as they did in Tennant and Karcher.

If it was possible to create a map with whole counties, and it was necessary to have a district with a greater deviation than 0.5%, it might well be be approved by the SCOTUS.

What has happened in Kirkpatrick v Preisler and Karcher v Daggett, is that the Missouri and New Jersey legislatures did not make a good faith effort to achieve equality.

In Kirkpatrick, the legislature claimed that they were making adjustments for non-resident population, and future growth.  But these were transparent guises.  When a plan was eventually drawn, it had the same deviation as that drawn by the legislature.

At the time of Karcher, 12 congressional plans had greater deviation than New Jersey, and 4 were of comparable magnitude.  But the New Jersey sloppily drew a partisan gerrymander, and tried to justify it on VRA grounds.

Where the Supreme Court has used the word "justify", the legislatures have tended to use "rationalization".

The SCOTUS has stated that there is no de minimis standard.  That means that it is impossible to determine whether larger ranges might be acceptable based on actual cases.

If I am going to justify a somewhat larger deviation,  I am going to have to show that my goal was to use whole counties, and that I had made a good faith effort in other portions of the state, where it was possible to achieve equality.   I can not demonstrate that with range.  I can with standard deviation.

I don't see any real evidence that the SCOTUS has expressed a preference for range over better and more appropriate measures of equality among multiple districts - it was just simpler for them to express their opinion.  In Karcher, they did make a comparison between two other districts.  They have also used average deviation - which is not a good idea either, since one can transfer from one overpopulated district to another even more overpopulated district with no penalty for the increased inequality.  Standard deviation penalizes collective disparity.

White v Regester has the actual house district populations in Texas.  They form a very nice normal distribution.   District populations since then have had worse and worse since then, approaching a uniform distribution.  

But the plan had an asymmetry in range.  It was possible to create one district with two counties that had a deviation of 5.8%, and there were no alternatives in compliance with the Texas Constitution.  At the same time there was a single county with a deviation of -4.7%.  Rather than violating the Texas Constitution by cutting a county.  They kept the 5.8% district, and violated the Texas Constitution by adding part of another county to the county that was naturally within the 5% limit, in a less egregious violation of the Texas Constitution, such that the overall range was 9.9%.  A good faith effort to achieve equality could have accepted the deviations of two districts at 5.8% and -4.7%.   Or the cut should have been applied to the 5.8% district (once a cut was made, it would have been possible to get much closer to 0.0% for that district.

And then they compounded their mistake by creating a multi-county district with a deviation of +5.7%, in an area where it was quite possible to have a district with near zero deviation.  That is, using total range permitted them to create another district with a larger deviation when it was absolutely not required.

Since then, range has been used to create or propose plans with greater overall inequality.  It is the wrong standard to use for measuring inequality.  There is no reason to dumb this down for the SCOTUS.

Note, I am not attempting to justify a 2.5% deviation for a Summit-Portage district.  I am permitting a larger deviation at this stage as part of a comprehensive method, devised in advance, as opposed to a post hoc rationalization of a legislature-drawn plan, that would:

(1) Be gerrymander resistant;
(2) Would largely adhere to political boundaries;
(3) Recognize larger metropolitan areas as significant communities of interest;
(4) Be reasonably compact; and
(5) Permit significant and real public participation.

Note that geographic compactness, may be simply one way to express conceptual integrity or concreteness.  Why are compact districts desirable?  It doesn't have anything to do with rubber bands.  It is because they are more likely to place neighbors with similar interests together.  An urban concentration is conceptually compact, as is a less urban area, even if it somewhat wraps around urban regions.

[muon2]

As I noted, the 5% is acceptable only for legislative districts when there is no stricter state standards. jimrtex favors a more relaxed standard for apportionment regions, but that is ineffective at reducing regular chops. For CDs the range can be up to 1% if the state can show consistently applied principles, and there is no smaller range using those same principles. A 0.5% deviation is an easy way to insure a range within 1%.

You're reading Tennant as narrowly as Karcher had been read.

Good faith effort can not be so narrowly defined as:

GOOD_FAITH = 0.005.

While avoiding a mini-chop which would have moved 15,000 persons.   You sliced between Portage and Summit.  You did not make a good faith effort to preserve that urban county cluster.

And range criteria is the wrong one to apply.  If you'd like, I'll show the MALC proposal for Texas House seats that cranked every Republican/Anglo seat up to 4.99%.  If the redistricting application displayed another digit, they would have gone to 4.999%.  Good faith is attempting to hit the bulls eye, and scoring 10 if you are within or even touching the ring.  Bad faith is to carry the red arrows down to the target, and insert them so that they are touching the ring.

I don't find any comfort in Tennant that a 5% variation would be permitted in congressional districts. The opinion said that a range of 0.79% was considered a minor deviation under Karcher and is still minor today, despite the ability of computers to create plans with less deviation. Since it is a minor deviation the state needed to show that the deviation was necessary to meet legitimate state objectives, not merely a good faith effort to meet those objectives. A 5% deviation for congressional districts has not been seen as minor to SCOTUS in the past, and there is nothing in the opinion to suggest that would change. I also reiterate that SCOTUS has consistently used population range, not percent deviation, to measure inequality between the largest and smallest district as they did in Tennant and Karcher.

If it was possible to create a map with whole counties, and it was necessary to have a district with a greater deviation than 0.5%, it might well be be approved by the SCOTUS.

What has happened in Kirkpatrick v Preisler and Karcher v Daggett, is that the Missouri and New Jersey legislatures did not make a good faith effort to achieve equality.

In Kirkpatrick, the legislature claimed that they were making adjustments for non-resident population, and future growth.  But these were transparent guises.  When a plan was eventually drawn, it had the same deviation as that drawn by the legislature.

At the time of Karcher, 12 congressional plans had greater deviation than New Jersey, and 4 were of comparable magnitude.  But the New Jersey sloppily drew a partisan gerrymander, and tried to justify it on VRA grounds.

Where the Supreme Court has used the word "justify", the legislatures have tended to use "rationalization".

The SCOTUS has stated that there is no de minimis standard.  That means that it is impossible to determine whether larger ranges might be acceptable based on actual cases.

If I am going to justify a somewhat larger deviation,  I am going to have to show that my goal was to use whole counties, and that I had made a good faith effort in other portions of the state, where it was possible to achieve equality.   I can not demonstrate that with range.  I can with standard deviation.

I don't see any real evidence that the SCOTUS has expressed a preference for range over better and more appropriate measures of equality among multiple districts - it was just simpler for them to express their opinion.  In Karcher, they did make a comparison between two other districts.  They have also used average deviation - which is not a good idea either, since one can transfer from one overpopulated district to another even more overpopulated district with no penalty for the increased inequality.  Standard deviation penalizes collective disparity.

White v Regester has the actual house district populations in Texas.  They form a very nice normal distribution.   District populations since then have had worse and worse since then, approaching a uniform distribution.  

But the plan had an asymmetry in range.  It was possible to create one district with two counties that had a deviation of 5.8%, and there were no alternatives in compliance with the Texas Constitution.  At the same time there was a single county with a deviation of -4.7%.  Rather than violating the Texas Constitution by cutting a county.  They kept the 5.8% district, and violated the Texas Constitution by adding part of another county to the county that was naturally within the 5% limit, in a less egregious violation of the Texas Constitution, such that the overall range was 9.9%.  A good faith effort to achieve equality could have accepted the deviations of two districts at 5.8% and -4.7%.   Or the cut should have been applied to the 5.8% district (once a cut was made, it would have been possible to get much closer to 0.0% for that district.

And then they compounded their mistake by creating a multi-county district with a deviation of +5.7%, in an area where it was quite possible to have a district with near zero deviation.  That is, using total range permitted them to create another district with a larger deviation when it was absolutely not required.

Since then, range has been used to create or propose plans with greater overall inequality.  It is the wrong standard to use for measuring inequality.  There is no reason to dumb this down for the SCOTUS.

Note, I am not attempting to justify a 2.5% deviation for a Summit-Portage district.  I am permitting a larger deviation at this stage as part of a comprehensive method, devised in advance, as opposed to a post hoc rationalization of a legislature-drawn plan, that would:

(1) Be gerrymander resistant;
(2) Would largely adhere to political boundaries;
(3) Recognize larger metropolitan areas as significant communities of interest;
(4) Be reasonably compact; and
(5) Permit significant and real public participation.

Note that geographic compactness, may be simply one way to express conceptual integrity or concreteness.  Why are compact districts desirable?  It doesn't have anything to do with rubber bands.  It is because they are more likely to place neighbors with similar interests together.  An urban concentration is conceptually compact, as is a less urban area, even if it somewhat wraps around urban regions.

I can easily accept a statistical measure for district inequality, but the issue the court has considered most important is the disparity between the largest and smallest districts. The relative size from the largest to smallest district was the issue in Reynolds v. Sims, not the average or standard deviation. The fact that there is a disparity in the value of a person's vote drives the decisions related to one man one vote, and the greatest disparity occurs when viewing the extreme cases among districts.

Consider the following hypothetical set of 20 districts with an ideal population of 100,000 persons in each. Two plans are submitted that comply with all state objectives. In plan A there are 10 districts with a population of 99,900 and 10 with a population of 100,100; giving a range of 200 (0.2%) and a standard deviation of 100 (0.100%). In plan B there are 19 districts with a population of 99,980 and one with a population of 100,380; giving a range of 400 (0.4%) and a standard deviation of 87.2 (0.087%). Plan B has the smaller standard deviation, but I find it unlikely that the court would ignore the fact that plan B has twice the maximum disparity present in plan A. So though I prefer standard deviation as a statistical measure, I think the law of one man one vote requires a range measure.

Other than the question of population deviation I think your principles are on target.

[jimrtex]

If I am going to justify a somewhat larger deviation,  I am going to have to show that my goal was to use whole counties, and that I had made a good faith effort in other portions of the state, where it was possible to achieve equality.   I can not demonstrate that with range.  I can with standard deviation.

I don't see any real evidence that the SCOTUS has expressed a preference for range over better and more appropriate measures of equality among multiple districts - it was just simpler for them to express their opinion.  In Karcher, they did make a comparison between two other districts.  They have also used average deviation - which is not a good idea either, since one can transfer from one overpopulated district to another even more overpopulated district with no penalty for the increased inequality.  Standard deviation penalizes collective disparity.

I can easily accept a statistical measure for district inequality, but the issue the court has considered most important is the disparity between the largest and smallest districts. The relative size from the largest to smallest district was the issue in Reynolds v. Sims, not the average or standard deviation. The fact that there is a disparity in the value of a person's vote drives the decisions related to one man one vote, and the greatest disparity occurs when viewing the extreme cases among districts.

Wesberry v Vandiver which was the lower court decision that was overturned by Wesberry v Sanders focused on relative deviation, which it erroneously referred to as "variance".   The plaintiffs in that case had suggested that Georgia should be limited to 15% relative deviation, and included in their evidence the number of districts across the country that exceeded 15% deviation, as well as 10% deviation.

In Wesberry v Sanders the SCOTUS noted both that the Atlanta district would have more than twice the average population (ie a relative deviation of more than 100%, and three times that of the smallest.   Georgia happened to be an egregious case where a district comprised of Fulton, DeKalb, and Rockdale had a population of twice the ideal, while the others were just sloppily unequal.

The Wesberry v Vandiver opinion said, "[w]e hasten to add that we neither expressly nor impliedly adopt any mathematical standard.  We know of no basis for an exact standard. ... Sanders v. Gray, supra, where sufficient basis existed. We use plaintiffs' suggested standard here in amplification of their contentions.  It is clear by any standard however that the population of the Fifth District is grossly out of balance with that of the other nine congressional districts of Georgia ..."

The SCOTUS opinion quoted "It is clear by any standard ...", and Justice Harlan in his dissent noted, "The Court's 'as nearly as is practicable' formula sweeps a host of questions under the rug. How great a difference between the populations of various districts within a State is tolerable? Is the standard an absolute or relative one, and, if the latter, to what is the difference in population to be related? Does the number of districts within the State have any relevance? Is the number of voters or the number of inhabitants controlling? Is the relevant statistic the greatest disparity between any two districts in the State, or the average departure from the average population per district, or a little of both? May the State consider factors such as area or natural boundaries (rivers, mountain ranges) which are plainly relevant to the practicability of effective representation?

There is an obvious lack of criteria for answering questions such as these, which points up the impropriety of the Court's wholehearted but heavy-footed entrance into the political arena."

The 1911 apportionment law stated that representatives "be elected by districts comprised of contiguous territory, and containing as nearly as practicable an equal number of inhabitants."  The "as nearly as practicable [equality]" language has found its way into the current legal standard, even though Congress appears to have deliberately removed it from the 1929 apportionment, and subsequent laws.  As Justice Harlan noted, it was as if the SCOTUS was saying that the 1911 standard would be applicable even if Congress had never passed a law at all.

Might Congress pass a law stating how equality was to be measured?  Of course.  And in the absence of congressional legislation, might a State legislature do the same?  Yes.

Use of range leads to mischievous inequality.

Consider the following hypothetical set of 20 districts with an ideal population of 100,000 persons in each. Two plans are submitted that comply with all state objectives. In plan A there are 10 districts with a population of 99,900 and 10 with a population of 100,100; giving a range of 200 (0.2%) and a standard deviation of 100 (0.100%). In plan B there are 19 districts with a population of 99,980 and one with a population of 100,380; giving a range of 400 (0.4%) and a standard deviation of 87.2 (0.087%). Plan B has the smaller standard deviation, but I find it unlikely that the court would ignore the fact that plan B has twice the maximum disparity present in plan A. So though I prefer standard deviation as a statistical measure, I think the law of one man one vote requires a range measure.

If these were the results of a physics experiment, you'd expect that the results had been fudged in either case, perhaps measuring instruments had less resolution than the displayed accuracy, or maybe some sort of quantization effect.

Let's try a different hypothetical.

Three plans are submitted: (Plan A) 10 districts with a population of 99,500 and 10 with a population of 100,500; giving a range of 1000 (1%) and a standard deviation of 500 (0.5%).  Plan B there are 19 districts with a population of 99,950 and one with a population of 100,950; giving a range of 1000 (1%) and a standard deviation of 300 (0.3%).   Plan C had districts of   100,139; 100,327; 100,103; 99,773; 99,948; 100,086; 100,500; 100,069; 100,109; 100,211;  100,335; 99,560; 99,738; 99,980; 100,002; 99,997; 99,752; 100,400; 99,558; and 99,413 giving a range of 1088 (1.088%) and a standard deviation of 287 (0.287%).

Plan A looks like that used in 1990s in Texas, where the Democratic seats in Harris County were uniformly underpopulated and the Republican seats were uniformly overpopulated; Plan B looks like that proposed by a rural legislator who didn't add Archer to Wichita county, as part of a plan to underpopulate West Texas districts, so that Harris County could be denied a representative.  In exchange, the Harris County Democrats were permitted to draw the districts in Harris County.

Plan C looks like someone used a spreadsheet to generate a normal distribution with a mean of 100,000, standard deviation of 250 (0.25%), knowing that there was a 64% chance of a district having a deviation greater than 0.5% (1 - 0.95²⁰), and an almost certainty that with enough district the range would be greater than 1%.

Which plan was a good faith effort to achieve equality, and which were the result of politicians with sticky fingers relying on the advice of lawyers?

[muon2]

We agree that one of the goals is significant and real public participation. I'd love to see statistical education get to the point where the standard deviation is as obvious to the public as the mean, but that day is far away. Standard deviation is just not a measure that is set up for public participation.

There's a reason that the legislatures and courts tend to use maximum deviation, average deviation or range, and that's because these are values they understand. Even if the Congress were to enact a standard for population inequality, and that standard were upheld by SCOTUS, I would be surprised if the choice is standard deviation.

It's true that the more accessible measures I mention allow for more obvious games to be played with district populations. A skilled mathematician can tilt the field with standard deviation, too. The point is that population inequality should be measured to show that after considering other criteria such as chops and erosity the plan has the least inequality. I'll rely on those other criteria to control gerrymandering. Thereafter I'd like the simplest measure to show the plan has addressed inequality. The courts have used range in many decisions, and it's simple to understand. Mathematically I found that it correlates slightly better than average deviation to the number of geographic units available to make a map.

[jimrtex]

We agree that one of the goals is significant and real public participation. I'd love to see statistical education get to the point where the standard deviation is as obvious to the public as the mean, but that day is far away. Standard deviation is just not a measure that is set up for public participation.

There's a reason that the legislatures and courts tend to use maximum deviation, average deviation or range, and that's because these are values they understand. Even if the Congress were to enact a standard for population inequality, and that standard were upheld by SCOTUS, I would be surprised if the choice is standard deviation.

It's true that the more accessible measures I mention allow for more obvious games to be played with district populations. A skilled mathematician can tilt the field with standard deviation, too. The point is that population inequality should be measured to show that after considering other criteria such as chops and erosity the plan has the least inequality. I'll rely on those other criteria to control gerrymandering. Thereafter I'd like the simplest measure to show the plan has addressed inequality. The courts have used range in many decisions, and it's simple to understand. Mathematically I found that it correlates slightly better than average deviation to the number of geographic units available to make a map.

I would use standard deviation and erosity as measures to (dis)qualify proposed plans, from which the general public, or a body representative of the general public may choose.

Here is a general outline of my process:

1) State agency (legislative council, secretary of state, state statistical agency) prepares data.  This may require coordination with the census bureau, and local governments well in advance of the census.  For example, if neighborhoods are used for forming districts in larger cities, they should be defined well in advance, so that they represent real communities of interest.

2) Census data release and massaged by state agency.

3a) Ordinary persons invited to prepare plans with apportionment regions.  The plan with the most regions, and the best equality and erosity becomes the target.

3b) Ordinary persons invited to prepare new or improved plans, with the target number of regions.

3c) Qualifying plans are identified.

4a) Large panels of voters vote on which plan they prefer.   The panels would be large enough to be statistically representative of the electorate.  Each panel member would be presented maps of the proposed apportionment regions that contained their residence.  Their ranking of a plan would be based solely on its effect on them personally.

4b) Best overall plan would be identified using Condorcet.   Within each apportionment region of the best overall plan, results would be re-evaluated to determine if voters in that region favor that plan.   That is, is their local concurrence with the statewide plan.

5) Iterate for areas of two or more adjacent regions, to determine whether there is a more amenable local plan that will fit withing the best overall plan.

6) Divide multi-district regions into single districts.

[muon2]

Returning to the issue of adjacent clusters I looked at MN.

Plan A puts the St Cloud cluster in with Mpls. In doing so I only need to add Rice to bring the Twin Cities region to within 0.16% of 5 CDs. The region range is 0.33% (st dev 0.12%). Within the TC there are the minimum 4 chops (2 Hennepin, Ramsey, Dakota) and CD 6 was kept more compact by going south into Hennepin rather than stretching east to the WI line.




Plan B keeps the St Cloud cluster separate from Mpls. The erosity is lower than in plan A but the region range inequality rises to 0.98% (st dev 0.42%). It also raises a question about subregions of a cluster. The Dakota county CD 2 could exist as a region unto itself, but requires counties outside the cluster yet within the CSA. Keeping it to counties within the CSA might be a desirable extension from the pure cluster subregion.




Both these seem like plausible plans using the hard rule, so I don't see a problem here.

[jimrtex]

Returning to the issue of adjacent clusters I looked at MN.

Plan A puts the St Cloud cluster in with Mpls. In doing so I only need to add Rice to bring the Twin Cities region to within 0.16% of 5 CDs. The region range is 0.33% (st dev 0.12%). Within the TC there are the minimum 4 chops (2 Hennepin, Ramsey, Dakota) and CD 6 was kept more compact by going south into Hennepin rather than stretching east to the WI line.

What happens if you take 5 out to Eden Prairie, 3 down to Brooklyn Center and Robbindale, and 6 more of NW Hennepin.  That is, a little more treating it as a 3-way split of Hennepin, as opposed to starting from Minneapolis and working outward.

Another possibility would be to pull 6 out of Hennepin entirely, and go into Anoka.  Or maybe Minneapolis-St. Paul.  If that happened you would probably need to put S.St.Paul with the rest of Dakota, and make a small chop into Carver out west.

I see an advantage of two stage process, is that simplifies the first stage.  A liability is that it could place you into a trap in the second stage.

An alternative would be to be too choose the "best" plans at the first stage, and then develop all of them at the second stage.  But how do you know what to prune at the first stage.  In a sense, you might not want the "best" plans, but the best of a diverse set.

Plan B keeps the St Cloud cluster separate from Mpls. The erosity is lower than in plan A but the region range inequality rises to 0.98% (st dev 0.42%). It also raises a question about subregions of a cluster. The Dakota county CD 2 could exist as a region unto itself, but requires counties outside the cluster yet within the CSA. Keeping it to counties within the CSA might be a desirable extension from the pure cluster subregion.




Both these seem like plausible plans using the hard rule, so I don't see a problem here.

I'm kind of wary using the CSA.  For example, how do you justify leaving out McLeod and Sibley?  Or what if the numbers worked out better to include Sibley and Goodhue, but not Rice and Le Sueur?

This map illustrates a pitfall of a 2-stage process.  It produces an arguably better Metro map, with each of the big 4 counties having their own district (2 for Hennepin), but could be a tougher sell for the rest of the state.  

[jimrtex]

Thinking out loud...

We can think of traditional districts comprised of whole counties as being like building a stone wall, where we fit different sized and shaped stones together to build a wall of roughly equal height.  Had the legislatures not been so careless in maintaining the walls, such that some were 9-feet high, and others tumbled over, we might still be using them.

Modern block-based districting is more like using a 3D printer, where we can create phantasmagorical creatures with infinite plasticity.

Iowa still does it the old way.   Why can they do it?  The stones are of modest size, none so large that by itself it is too large.  And even when they are moderately large, they are dispersed in a way  that when the wall is build we can use them in different parts of the wall.  Iowa also uses limestone, so that the stones look almost like bricks, giving the surfaces of the wall a flat appearance, akin to might be achieved with bricks or sawn logs.

But can we pre-cut the larger stones, boulders really?  Perhaps at least score them so that they are easily cut?

So in Minnesota, we would have to precut Hennepin.  But it probably wouldn't hurt to cut Ramsey, Anoka, Washington, and Dakota.   What are the rules?  Counties of a certain size?  Or counties of a certain size within proximity of others?  Polk County, IA has more population than either Dakota or Anoka, and nearly as much as Ramsey.  Perhaps there could be a local option, the folks in Sherburne or western Stearns might prefer to be split, while those in Olmsted rigidly insist in being in the same district.

Or do we provide cuts of Polk County, IA, and add some rules that discourage their use?  Perhaps cutting of a county would have more of a penalty.  We can limit county cuts to more than is necessary, ... or reasonable, which might permit a double cut of Hennepin County.

A rule might be: max (2, ceil (pop/quota + 0.5))

Instead of apportionment regions based on whole counties, they could be based on whole building blocks covering an urbanized area.   This would provide a dividing line between the St.Cloud and Twin Cities sphere of influence in Sherburne County.

We don't want equal sized stones.  It is easier to fit them together when there is variation.  So splitting on townships, and maybe gathering smaller sized cities together works.

As an alternative, what if if we first created districts of more equal size, where the number is an integer multiple of the number of congressional districts.  These initial districts would be closer to the size of legislative districts, and we could apportion them to whole counties.   We would then assemble them to form a congressional district.  Perhaps some adjustment would be needed to get better equality, but maybe not.  While some of these preliminary districts might have a deviation of 5%, it is unlikely that all those assembled would have a collective deviation so large.  I suspect we would be down below 2%.

Some possible integers:

8 - a power of two which would permit pairwise merging.  Simple, but might result in elongated districts where they are joined end to end.

9 - a power of three, which might permit trio-wise merging, and more circular or square districts.

10 - easy to count on our fingers.

11 - maybe the reasons for a factorable number are bogus.

12 - factorable by 2 and 3, and 6, does this lead to hexagonal districts?

All 5?  Create 5 alternatives and vote on them?

This latter scheme might also be useful with respect to the VRA.  The initial smaller districts need not be drawn as obsessively based on race, and it may be possible to combine them to form congressional districts that are not strictly contiguous.

[Torie]

Plan B is considerably superior, and I oppose going for more erosity to get the size of the micro-chops down (I assume that when you talk about the population of regions (which I still think of as a convenience tool as opposed to anything substantive riding on it, other than finding the micr0-chops) that you talking about the size of the micro-chops.

[jimrtex]

This map shows the metropolitan statistical areas in the southeastern USA.  A metropolitan statistical area is based on a core of an urbanized area (ie urban area of 50,000 or more persons).  The MSA includes the counties that contain the core urbanized area (central counties), as well as outlying counties with significant commuting to or from the central counties. 

The outlying counties may themselves contain urbanized areas or urban clusters which would have qualified them to be the central counties of a metropolitan or micropolitan statistical area, but were captured by a stronger core.  These may be thought to be more like satellite cities and larger towns, rather than suburbs.  Nonetheless they represent an urban setting with strong economic ties to the central counties.

Outlying counties may also contain smaller urban clusters (less than 10,000 persons) or have no urban population (totally rural).  Essentially, these areas provide relatively few jobs, but are within commuting distance of the central counties.  These counties typically have few residents, and their exclusion from the urban county cluster has little effect on the metropolitan population.   They might be included in a congressional district based on a metropolitan area, based on their proximity, but it is not essential.   And the identification with the "big city" for these more rural areas may be relatively weak.

In the tables that follow, counties are classified based on the urban area with the largest share of the county's population.

NUA: No Urban Area.  The county is totally rural.

NQUA: Non-qualifying urban area.  The urban area with the largest share of the county population has fewer than 10,000 persons total, or more a small isolated town in a largely rural setting.

NQC: Non-qualifying core.   The urban area with the largest share of the county population has more than 10,000 persons total, but fewer than 5,000 in the county (or less than 50% for counties of 10,000 or less persons).  These counties do not qualify as a central county, but represent more of a small overlap of a core area into the county, and are not that dissimilar from the previous classifications.

The above 3 classifications are shown in a lighter shade on the map, and shown in red in the tables.  They represent the least urban, more peripheral counties of a metropolitan area.

UC: Core area is an urban cluster with a population of greater than 10,000.  It represents a larger town, that could have served as the core of a micropolitan statistical area, had not the county been captured by the metropolitan area.

UA: Core area for county is an urbanized area, which always have a population greater than 50,000.  The urbanized area need not be the core for the metropolitan area.  Census Bureau delineation procedures protect urbanized areas that have grown together, so such an urbanized area can not truly be regarded as independent or separate, particularly given the commuting ties.

The following tables represent the portion of metropolitan areas within each state.  Metropolitan statistical areas are delineated without regard to state boundaries, but for redistricting purposes, only the area within each state is of interest.  The first number is the population of the metropolitan area within the state (in thousands), while the second number is the population excluding the more peripheral counties.  The number in parentheses is the number of counties, within the state, that are in the metropolitan area.

For each county, the county population (in thousands), and classification code are shown.

Alabama

Birmingham-Hoover, AL 1128  1004  (7): Jefferson County 658 UA; Shelby County 195 UA; St. Clair County 84 UC; Walker County 67 UC; Blount County 57 NQUA; Chilton County 44 NQUA; and Bibb County 23 NQUA.

Huntsville, AL 418  418  (2): Madison County 335 UA; and Limestone County 83 UC.

Mobile, AL 413  413  (1): Mobile County 413 UA.

Montgomery, AL 375  363  (4): Montgomery County 229 UA; Elmore County 79 UA; Autauga County 55 UA; and Lowndes County 11 NUA.

Tuscaloosa, AL 230  195  (3): Tuscaloosa County 195 UA; Pickens County 20 NUA; and Hale County 16 NQUA.

Daphne-Fairhope-Foley, AL 182  182  (1): Baldwin County 182 UA.

Decatur, AL 154  119  (2): Morgan County 119 UA; and Lawrence County 34 NQUA.

Florence-Muscle Shoals, AL 147  147  (2): Lauderdale County 93 UA; and Colbert County 54 UA.

Dothan, AL 146  102  (3): Houston County 102 UA; Geneva County 27 NQUA; and Henry County 17 NQUA.

Auburn-Opelika, AL 140  140  (1): Lee County 140 UA.

Anniston-Oxford-Jacksonville, AL 119  119  (1): Calhoun County 119 UA.

Gadsden, AL 104  104  (1): Etowah County 104 UA.

Columbus, GA-AL 53  53  (1): Russell County 53 UA.


Arkansas

Little Rock-North Little Rock-Conway, AR 700  671  (6): Pulaski County 383 UA; Faulkner County 113 UA; Saline County 107 UA; Lonoke County 68 UA; Grant County 18 NQUA; and Perry County 10 NUA.

Fayetteville-Springdale-Rogers, AR-MO 440  424  (3): Benton County 221 UA; Washington County 203 UA; and Madison County 16 NUA.

Fort Smith, AR-OK 188  188  (2): Sebastian County 126 UA; and Crawford County 62 UA.

Jonesboro, AR 121  96  (2): Craighead County 96 UA; and Poinsett County 25 NQUA.

Pine Bluff, AR 100  77  (3): Jefferson County 77 UA; Lincoln County 14 NUA; and Cleveland County 9 NUA.

Hot Springs, AR 96  96  (1): Garland County 96 UA.

Texarkana, TX-AR 57  43  (2): Miller County 43 UA; and Little River County 13 NQUA.

Memphis, TN-MS-AR 51  51  (1): Crittenden County 51 UA.


Florida

Miami-Fort Lauderdale-West Palm Beach, FL 5565  5565  (3): Miami-Dade County 2496 UA; Broward County 1748 UA; and Palm Beach County 1320 UA.

Tampa-St. Petersburg-Clearwater, FL 2783  2783  (4): Hillsborough County 1229 UA; Pinellas County 917 UA; Pasco County 465 UA; and Hernando County 173 UA.

Orlando-Kissimmee-Sanford, FL 2134  2134  (4): Orange County 1146 UA; Seminole County 423 UA; Lake County 297 UA; and Osceola County 269 UA.

Jacksonville, FL 1346  1346  (5): Duval County 864 UA; Clay County 191 UA; St. Johns County 190 UA; Nassau County 73 UC; and Baker County 27 UC.

North Port-Sarasota-Bradenton, FL 702  702  (2): Sarasota County 379 UA; and Manatee County 323 UA.

Cape Coral-Fort Myers, FL 619  619  (1): Lee County 619 UA.

Lakeland-Winter Haven, FL 602  602  (1): Polk County 602 UA.

Deltona-Daytona Beach-Ormond Beach, FL 590  590  (2): Volusia County 495 UA; and Flagler County 96 UA.

Palm Bay-Melbourne-Titusville, FL 543  543  (1): Brevard County 543 UA.

Pensacola-Ferry Pass-Brent, FL 449  449  (2): Escambia County 298 UA; and Santa Rosa County 151 UA.

Port St. Lucie, FL 424  424  (2): St. Lucie County 278 UA; and Martin County 146 UA.

Tallahassee, FL 367  275  (4): Leon County 275 UA; Gadsden County 46 NQUA; Wakulla County 31 NQUA; and Jefferson County 15 NUA.

Ocala, FL 331  331  (1): Marion County 331 UA.

Naples-Immokalee-Marco Island, FL 322  322  (1): Collier County 322 UA.

Gainesville, FL 264  247  (2): Alachua County 247 UA; and Gilchrist County 17 NQUA.

Crestview-Fort Walton Beach-Destin, FL 236  236  (2): Okaloosa County 181 UA; and Walton County 55 UA.

Panama City, FL 185  169  (2): Bay County 169 UA; and Gulf County 16 NQUA.

Punta Gorda, FL 160  160  (1): Charlotte County 160 UA.

Homosassa Springs, FL 141  141  (1): Citrus County 141 UA.

Sebastian-Vero Beach, FL 138  138  (1): Indian River County 138 UA.

Sebring, FL 99  99  (1): Highlands County 99 UA.

The Villages, FL 93  93  (1): Sumter County 93 UA.

[muon2]

The next one I'd like to look at is LA. It has some clusters in close proximity and VRA concerns as well. Here's what I understand are the clusters on the map.

New Orleans (1.546) Jefferson, Orleans, Plaquemines, St Bernard, St Charles, St John the Baptist, St Tammany
Baton Rouge (0.970) Ascension, East Baton Rouge, Iberville, Livingston, West Baton Rouge (Iberville is on the map, but it should be off with the revised definition since the urban population is under 50% bringing the cluster to 0.925)
Shreveport (0.492) Bossier, Caddo
Lafayette (0.390) Iberia, Lafayette (but should this be disallowed due to a lack of connectivity?)
Houma (0.276) Lafourche, Terrebonne

The key is that one of the regions will have to contain a VRA district with >50% BVAP.

[jimrtex]

Georgia

Atlanta-Sandy Springs-Roswell, GA 5287  5081  (29): Fulton County 921 UA; Gwinnett County 805 UA; DeKalb County 692 UA; Cobb County 688 UA; Clayton County 259 UA; Cherokee County 214 UA; Henry County 204 UA; Forsyth County 176 UA; Paulding County 142 UA; Douglas County 132 UA; Coweta County 127 UA; Carroll County 111 UC; Fayette County 107 UA; Bartow County 100 UA; Newton County 100 UA; Rockdale County 85 UA; Walton County 84 UA; Barrow County 69 UC; Spalding County 64 UA; Pickens County 29 NQUA; Haralson County 29 NQUA; Butts County 24 NQUA; Dawson County 22 NQC; Meriwether County 22 NQUA; Lamar County 18 NQUA; Pike County 18 NQC; Morgan County 18 NQUA; Jasper County 14 NQUA; and Heard County 12 NUA.

Augusta-Richmond County, GA-SC 378  325  (5): Richmond County 201 UA; Columbia County 124 UA; Burke County 23 NQUA; McDuffie County 22 NQUA; and Lincoln County 8 NUA.

Savannah, GA 348  348  (3): Chatham County 265 UA; Effingham County 52 UC; and Bryan County 30 UA.

Columbus, GA-AL 242  201  (4): Muscogee County 190 UA; Harris County 32 NQC; Chattahoochee County 11 UA; and Marion County 9 NUA.

Macon, GA 232  156  (5): Bibb County 156 UA; Jones County 29 NQC; Monroe County 26 NQUA; Crawford County 13 NUA; and Twiggs County 9 NUA.

Athens-Clarke County, GA 193  150  (4): Clarke County 117 UA; Oconee County 33 UA; Madison County 28 NQC; and Oglethorpe County 15 NQC.

Gainesville, GA 180  180  (1): Hall County 180 UA.

Warner Robins, GA 180  168  (3): Houston County 140 UA; Peach County 28 UC; and Pulaski County 12 NQUA.

Albany, GA 157  123  (5): Dougherty County 95 UA; Lee County 28 UA; Worth County 22 NQUA; Terrell County 9 NQUA; and Baker County 3 NUA.

Chattanooga, TN-GA 149  133  (3): Walker County 69 UA; Catoosa County 64 UA; and Dade County 17 NQUA.

Dalton, GA 142  142  (2): Whitfield County 103 UA; and Murray County 40 UA.

Valdosta, GA 140  109  (4): Lowndes County 109 UA; Brooks County 16 NQUA; Lanier County 10 NQUA; and Echols County 4 NUA.

Brunswick, GA 112  80  (3): Glynn County 80 UA; Brantley County 18 NQC; and McIntosh County 14 NQUA.

Rome, GA 96  96  (1): Floyd County 96 UA.

Hinesville, GA 78  63  (2): Liberty County 63 UA; and Long County 14 NQC.


Louisiana

New Orleans-Metairie, LA 1190  1190  (8): Jefferson Parish 433 UA; Orleans Parish 344 UA; St. Tammany Parish 234 UA; St. Charles Parish 53 UA; St. John the Baptist Parish 46 UA; St. Bernard Parish 36 UA; Plaquemines Parish 23 UA; and St. James Parish 22 UC.

Baton Rouge, LA 802  733  (9): East Baton Rouge Parish 440 UA; Livingston Parish 128 UA; Ascension Parish 107 UA; Iberville Parish 33 UA; West Baton Rouge Parish 24 UA; Pointe Coupee Parish 23 NQUA; East Feliciana Parish 20 NUA; West Feliciana Parish 16 NUA; and St. Helena Parish 11 NUA.

Lafayette, LA 467  467  (5): Lafayette Parish 222 UA; Iberia Parish 73 UA; Acadia Parish 62 UC; Vermilion Parish 58 UC; and St. Martin Parish 52 UC.

Shreveport-Bossier City, LA 440  413  (4): Caddo Parish 255 UA; Bossier Parish 117 UA; Webster Parish 41 UC; and De Soto Parish 27 NQUA.

Houma-Thibodaux, LA 208  208  (2): Terrebonne Parish 112 UA; and Lafourche Parish 96 UA.

Lake Charles, LA 200  193  (2): Calcasieu Parish 193 UA; and Cameron Parish 7 NUA.

Monroe, LA 176  154  (2): Ouachita Parish 154 UA; and Union Parish 23 NQUA.

Alexandria, LA 154  132  (2): Rapides Parish 132 UA; and Grant Parish 22 NQC.

Hammond, LA 121  121  (1): Tangipahoa Parish 121 UA.


Mississippi

Jackson, MS 567  510  (6): Hinds County 245 UA; Rankin County 142 UA; Madison County 95 UA; Copiah County 29 NQUA; Yazoo County 28 UC; and Simpson County 28 NQUA.

Gulfport-Biloxi-Pascagoula, MS 371  371  (3): Harrison County 187 UA; Jackson County 140 UA; and Hancock County 44 UA.

Memphis, TN-MS-AR 247  161  (5): DeSoto County 161 UA; Marshall County 37 NQUA; Tate County 29 NQUA; Tunica County 11 NQUA; and Benton County 9 NUA.

Hattiesburg, MS 143  131  (3): Forrest County 75 UA; Lamar County 56 UA; and Perry County 12 NUA.


North Carolina

Charlotte-Concord-Gastonia, NC-SC 1881  1881  (7): Mecklenburg County 920 UA; Gaston County 206 UA; Union County 201 UA; Cabarrus County 178 UA; Iredell County 159 UA; Rowan County 138 UA; and Lincoln County 78 UC.

Raleigh, NC 1130  1070  (3): Wake County 901 UA; Johnston County 169 UA; and Franklin County 61 NQC.

Greensboro-High Point, NC 724  724  (3): Guilford County 488 UA; Randolph County 142 UC; and Rockingham County 94 UC.

Winston-Salem, NC 641  602  (5): Forsyth County 351 UA; Davidson County 163 UA; Stokes County 47 UA; Davie County 41 UA; and Yadkin County 38 NQUA.

Durham-Chapel Hill, NC 504  401  (4): Durham County 268 UA; Orange County 134 UA; Chatham County 64 NQUA; and Person County 39 NQUA.

Asheville, NC 425  404  (4): Buncombe County 238 UA; Henderson County 107 UA; Haywood County 59 UA; and Madison County 21 NQC.

Fayetteville, NC 366  366  (2): Cumberland County 319 UA; and Hoke County 47 UA.

Hickory-Lenoir-Morganton, NC 365  328  (4): Catawba County 154 UA; Burke County 91 UA; Caldwell County 83 UA; and Alexander County 37 NQUA.

Wilmington, NC 255  255  (2): New Hanover County 203 UA; and Pender County 52 UC.

Jacksonville, NC 178  178  (1): Onslow County 178 UA.

Greenville, NC 168  168  (1): Pitt County 168 UA.

Rocky Mount, NC 152  152  (2): Nash County 96 UA; and Edgecombe County 57 UA.

Burlington, NC 151  151  (1): Alamance County 151 UA.

New Bern, NC 127  104  (3): Craven County 104 UA; Pamlico County 13 NUA; and Jones County 10 NUA.

Goldsboro, NC 123  123  (1): Wayne County 123 UA.

Myrtle Beach-Conway-North Myrtle Beach, SC-NC 107  107  (1): Brunswick County 107 UA.

Virginia Beach-Norfolk-Newport News, VA-NC 36  0  (2): Currituck County 24 NQC; and Gates County 12 NUA.

[jimrtex]

The next one I'd like to look at is LA. It has some clusters in close proximity and VRA concerns as well. Here's what I understand are the clusters on the map.

New Orleans (1.546) Jefferson, Orleans, Plaquemines, St Bernard, St Charles, St John the Baptist, St Tammany
Baton Rouge (0.970) Ascension, East Baton Rouge, Iberville, Livingston, West Baton Rouge (Iberville is on the map, but it should be off with the revised definition since the urban population is under 50% bringing the cluster to 0.925)
Shreveport (0.492) Bossier, Caddo
Lafayette (0.390) Iberia, Lafayette (but should this be disallowed due to a lack of connectivity?)
Houma (0.276) Lafourche, Terrebonne

The key is that one of the regions will have to contain a VRA district with >50% BVAP.

Yes Iberville is off under revised criteria.

The Iberia-Lafayette border is about 16% of the square root of the smaller county (Lafayette) so qualifies.  Moreover it is right on the direct route from Lafayette to New Iberia on the high not-so-low ground to the west of the Atchafalaya.

Maybe it demonstrates that Louisiana fails the Gingles test.

[jimrtex]

Oklahoma

Oklahoma City, OK 1253  1184  (7): Oklahoma County 719 UA; Cleveland County 256 UA; Canadian County 116 UA; Grady County 52 UC; Logan County 42 UA; McClain County 35 NQUA; and Lincoln County 34 NQUA.

Tulsa, OK 937  921  (7): Tulsa County 603 UA; Rogers County 87 UC; Wagoner County 73 UA; Creek County 70 UA; Osage County 47 UA; Okmulgee County 40 UC; and Pawnee County 17 NQUA.

Lawton, OK 130  124  (2): Comanche County 124 UA; and Cotton County 6 NQUA.

Fort Smith, AR-OK 93  0  (2): Le Flore County 50 NQUA; and Sequoyah County 42 NQUA.


South Carolina

Greenville-Anderson-Mauldin, SC 824  824  (4): Greenville County 451 UA; Anderson County 187 UA; Pickens County 119 UA; and Laurens County 67 UC.

Columbia, SC 768  709  (6): Richland County 385 UA; Lexington County 262 UA; Kershaw County 62 UC; Fairfield County 24 NQUA; Saluda County 20 NQUA; and Calhoun County 15 NUA.

Charleston-North Charleston, SC 665  665  (3): Charleston County 350 UA; Berkeley County 178 UA; and Dorchester County 137 UA.

Charlotte-Concord-Gastonia, NC-SC 336  303  (3): York County 226 UA; Lancaster County 77 UC; and Chester County 33 NQUA.

Spartanburg, SC 313  313  (2): Spartanburg County 284 UA; and Union County 29 UC.

Myrtle Beach-Conway-North Myrtle Beach, SC-NC 269  269  (1): Horry County 269 UA.

Florence, SC 206  206  (2): Florence County 137 UA; and Darlington County 69 UC.

Augusta-Richmond County, GA-SC 187  160  (2): Aiken County 160 UA; and Edgefield County 27 NQUA.

Hilton Head Island-Bluffton-Beaufort, SC 187  162  (2): Beaufort County 162 UA; and Jasper County 25 NQUA.

Sumter, SC 107  107  (1): Sumter County 107 UA.


Tennessee

Nashville-Davidson--Murfreesboro--Franklin, TN 1671  1544  (14): Davidson County 627 UA; Rutherford County 263 UA; Williamson County 183 UA; Sumner County 161 UA; Wilson County 114 UA; Maury County 81 UC; Robertson County 66 UC; Dickson County 50 UC; Cheatham County 39 NQUA; Hickman County 25 NUA; Macon County 22 NQUA; Smith County 19 NQUA; Cannon County 14 NQUA; and Trousdale County 8 NUA.

Memphis, TN-MS-AR 1027  989  (3): Shelby County 928 UA; Tipton County 61 UC; and Fayette County 38 NQUA.

Knoxville, TN 838  774  (9): Knox County 432 UA; Blount County 123 UA; Anderson County 75 UA; Roane County 54 UC; Loudon County 49 UA; Campbell County 41 UC; Grainger County 23 NUA; Morgan County 22 NQC; and Union County 19 NUA.

Chattanooga, TN-GA 379  336  (3): Hamilton County 336 UA; Marion County 28 NQUA; and Sequatchie County 14 NQUA.

Kingsport-Bristol-Bristol, TN-VA 214  214  (2): Sullivan County 157 UA; and Hawkins County 57 UA.

Johnson City, TN 199  180  (3): Washington County 123 UA; Carter County 57 UA; and Unicoi County 18 NQUA.

Clarksville, TN-KY 172  172  (1): Montgomery County 172 UA.

Jackson, TN 130  98  (3): Madison County 98 UA; Chester County 17 NQUA; and Crockett County 15 NQUA.

Cleveland, TN 116  99  (2): Bradley County 99 UA; and Polk County 17 NUA.

Morristown, TN 114  114  (2): Hamblen County 63 UA; and Jefferson County 51 UA.


Texas

Dallas-Fort Worth-Arlington, TX 6426  6359  (13): Dallas County 2368 UA; Tarrant County 1809 UA; Collin County 782 UA; Denton County 663 UA; Johnson County 151 UA; Ellis County 150 UA; Parker County 117 UC; Kaufman County 103 UC; Hunt County 86 UC; Rockwall County 78 UA; Wise County 59 NQUA; Hood County 51 UC; and Somervell County 8 NUA.

Houston-The Woodlands-Sugar Land, TX 5920  5849  (9): Harris County 4092 UA; Fort Bend County 585 UA; Montgomery County 456 UA; Brazoria County 313 UA; Galveston County 291 UA; Liberty County 76 UC; Waller County 43 NQUA; Chambers County 35 UA; and Austin County 28 NQUA.

San Antonio-New Braunfels, TX 2143  2033  (8): Bexar County 1715 UA; Guadalupe County 132 UA; Comal County 108 UA; Medina County 46 NQUA; Atascosa County 45 UC; Wilson County 43 NQUA; Kendall County 33 UC; and Bandera County 20 NUA.

Austin-Round Rock, TX 1716  1716  (5): Travis County 1024 UA; Williamson County 423 UA; Hays County 157 UA; Bastrop County 74 UC; and Caldwell County 38 UC.

El Paso, TX 804  801  (2): El Paso County 801 UA; and Hudspeth County 3 NUA.

McAllen-Edinburg-Mission, TX 775  775  (1): Hidalgo County 775 UA.

Corpus Christi, TX 428  428  (3): Nueces County 340 UA; San Patricio County 65 UA; and Aransas County 23 UC.

Brownsville-Harlingen, TX 406  406  (1): Cameron County 406 UA.

Killeen-Temple, TX 405  386  (3): Bell County 310 UA; Coryell County 75 UA; and Lampasas County 20 NQUA.

Beaumont-Port Arthur, TX 403  389  (4): Jefferson County 252 UA; Orange County 82 UA; Hardin County 55 UA; and Newton County 14 NUA.

Lubbock, TX 291  279  (3): Lubbock County 279 UA; Crosby County 6 NUA; and Lynn County 6 NQUA.

Waco, TX 253  235  (2): McLennan County 235 UA; and Falls County 18 NQUA.

Amarillo, TX 252  242  (5): Potter County 121 UA; Randall County 121 UA; Carson County 6 NQUA; Oldham County 2 NUA; and Armstrong County 2 NUA.

Laredo, TX 250  250  (1): Webb County 250 UA.

College Station-Bryan, TX 229  195  (3): Brazos County 195 UA; Burleson County 17 NQUA; and Robertson County 17 NQUA.

Longview, TX 214  175  (3): Gregg County 122 UA; Rusk County 53 UC; and Upshur County 39 NQUA.

Tyler, TX 210  210  (1): Smith County 210 UA.

Abilene, TX 165  132  (3): Taylor County 132 UA; Jones County 20 NQUA; and Callahan County 14 NQUA.

Wichita Falls, TX 151  132  (3): Wichita County 132 UA; Clay County 11 NQUA; and Archer County 9 NQC.

Midland, TX 142  137  (2): Midland County 137 UA; and Martin County 5 NUA.

Odessa, TX 137  137  (1): Ector County 137 UA.

Sherman-Denison, TX 121  121  (1): Grayson County 121 UA.

San Angelo, TX 112  110  (2): Tom Green County 110 UA; and Irion County 2 NUA.

Victoria, TX 94  87  (2): Victoria County 87 UA; and Goliad County 7 NUA.

Texarkana, TX-AR 93  93  (1): Bowie County 93 UA.

[muon2]

Does this reflect another set of criteria for consideration as urban county clusters? It would be helpful to concentrate on one version to see if it has any obvious weaknesses. I'm OK with your earlier definition for now, though a map that just has those qualifying multicounty clusters would be useful.

[Torie]

The urban cluster definition has changed exactly how?  And the overlay is designed to solve exactly what problem? Jimtex's musings are just incomprehensible to the layperson.

[jimrtex]

Does this reflect another set of criteria for consideration as urban county clusters? It would be helpful to concentrate on one version to see if it has any obvious weaknesses. I'm OK with your earlier definition for now, though a map that just has those qualifying multicounty clusters would be useful.

No.  I am showing the development from the beginning, starting with Metropolitan Statistical Areas.  My earlier maps had simply ignored the more rural counties and showed what was left.  Torie had said he wanted to look at all multi-county MSA.

So starting with all counties in each MSA:

(1) Exclude counties with no urban population.
(2) Exclude counties whose urban area with the largest population in the county has less than 10,000 total, and thus does not qualify as a core.
(3) Exclude counties whose urban area with the largest population in the county have less than 5,000 in the county (less than 50% for smaller counties), and also do not qualify to be a central county.

These counties are included in a MSA solely based on commuting.  In many cases this occurs precisely because they don't have much urban population, and relatively few local jobs.  Small towns at the same distance from the city will have more local jobs, some retail, perhaps doctors, etc., perhaps a small manufacturing plant, and relatively less commuting (commuting is based on percentage of a residents who work in the central counties).  If you had a map with arrows showing absolute magnitude of commuting flow, these areas would have skinny arrows, compared to adjoining "non-metropolitan" counties.  If there were a thematic map showing commuting percentages, there would only small variation.  But the definition reduces this information to a True/False value.

These excluded counties are shown as a lighter shade on the map.

[Torie]

Is the above definition different from the urban cluster definition provided by the census?  I thought the lighter shade counties were as defined by the census for non core counties or whatever the terminology was.

[jimrtex]

The urban cluster definition has changed exactly how?  And the overlay is designed to solve exactly what problem? Jimtex's musings are just incomprehensible to the layperson.

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The latest maps show all Metropolitan Statistical Areas.   It does not show Micropolitan Statistical Areas (both are CBSA).   It does include single-county MSA.  You should be able to ignore those without too much problem.   I think it is helpful to show them, as part of the process of understanding the derivation of urban county clusters.

Please note: "urban cluster" is a specific Census Bureau term for smaller "urban area", those with a population less than 50,000.   Before 2000, the census bureau had defined "urbanized area", which had a population greater than 50,000, and were intended to represent the suburban fringe around cities.

In 2000, they extended the concept to smaller populations, along with changing the rules for how they were delineated.  They retained the term "urbanized area" for larger areas, and to maintain comparability, added an over-arching term of "urban area" to include all areas, and "urban clusters" for smaller areas.

[Torie]

OK thanks then Jimtex. No change. We are still talking about, for redistricting purposes, multi county "urban areas" as defined by the Census Bureau, and nothing more. This is a Goldilocks issue - too many multi county urban areas, and it could spit out a map mess, too few and too many urban chops, and too much gerrymandering potential. But you have come up with something where coincidentally or not, it sails between the Scylla and Charybdis, and comes out just about right - statistics and intuition for at least one time harmoniously coincide. Now if we could just get to the same place with erosity, life would be beautiful.