Procedurally Generated Districts in West Virginia

I have thought about the issue of districting in elections. I think I may have come up with a way to draw districts procedurally (read: randomly following some rules).



In order to do this in a way that disregards county lines as required by the Constitution, I would have to do this using precincts (I think). However, given that this is just a demonstration and gathering all the information for which precincts are adjacent to which and their relative populations, I have used the counties as stand ins.



First I took the list of counties and fed them through random.org to randomize them. I got the following result:



Hampshire

Morgan

Brooke

Harrison

Randolph

Mercer

Lewis

Marshall

McDowell

Logan

Pocahontas

Webster

Kanawha

Berkeley

Nicholas

Upshur

Cabell

Monroe

Marion

Hardy

Calhoun

Hancock

Grant

Wood

Ohio

Doddridge

Taylor

Fayette

Greenbrier

Mason

Wayne

Pleasants

Monongalia

Pendleton

Raleigh

Mineral

Wetzel

Wirt

Boone

Ritchie

Jefferson

Mingo

Clay

Jackson

Tucker

Roane

Summers

Gilmer

Wyoming

Putnam

Lincoln

Braxton

Preston

Tyler

Barbour

So I started the first district with Hampshire. The first county on the randomized list.



DISTRICT 1

COUNTY POPUL RUNNING POP. SMALLEST REMAINING ADJACENCIES



HAMPSHIRE 24.0K 24.0K MINERAL, MORGAN



We look at counties adjacent to Hampshire and pick the counties that have the fewest remaining adjacent counties so as to prevent non-adjacent districts (stranding the panhandle counties). Of Mineral and Morgan, we choose the one that is highest on our random list. In this case it is Morgan.



DISTRICT 1

COUNTY POPUL RUNNING PO. SMALLEST REMAINING ADJACENCIES



HAMPSHIRE 24.0K 24.0K MINERAL, MORGAN

MORGAN 17.5K 41.5K MINERAL, BERKELEY

Now Mineral and Berkeley have the smallest remaining adjacencies. Berkeley is higher on the list. So we choose it next and continue until we reach one-third of the population.



DISTRICT 1

COUNTY POPUL RUNNING POPULAITON SMALLEST REMAINING ADJACENCIES



HAMPSHIRE 24.0K 24.0K MINERAL, MORGAN

MORGAN 17.5K 41.5K MINERAL, BERKELEY

BERKELEY 104.2K 145.7K MINERAL, JEFFERSON

MINERAL 28.2K 167.9K JEFFERSON

JEFFERSON 53.5K 221.4K HARDY

HARDY 14.0K 235.4K GRANT, PENDELTON

GRANT 11.9K 247.3K PENDLETON

PENDELTON 7.7K 255.0K TUCKER

TUCKER 7.1K 262.1K POCAHONTAS

POCAHONTAS 8.7K 270.8K PRESTON, RANDOLPH

RANDOLPH 29.4K 300.2K PRESTON

PRESTON 33.5K 335.7K MONONGALIA, BARBOUR

MONONGALIA 96.2K 431.9K BARBOUR, TAYLOR, MARION

MARION 56.4K 488.3K TAYLOR

TAYLOR 16.9K 505.2K BARBOUR

BARBOUR 16.6K 521.8K UPSHUR

UPSHUR 24.3K 546.1K HARRISON

HARRISON 69.1K 615.2K WETZEL

---------------------- would exceed district size

After selecting the first district, we would choose the highest remaining county. In this case, it is Brooke.



DISTRICT 2

COUNTY POPUL RUNNING POP. SMALLEST REMAINING ADJACENCIES



BROOKE 24.1K 24.1K HANCOCK

Then, we check adjacencies and pick the one with the fewest adjacencies, using the list to break ties and we get District 2 being:



DISTRICT 2

COUNTY POPUL RUNNING POP SMALLEST REMAINING ADJACENCIES



BROOKE 24.1K 24.1K HANCOCK

HANCOCK 30.7K 54.8K OHIO

OHIO 44.4K 99.2K WETZEL

WETZEL 16.6K 115.8K TYLER

TYLER 9.2K 125.0K PLEASANTS

PLEASANTS 7.6K 132.6K WOOD, DODDRIDGE

WOOD 87.0K 219.0K DODDRIDGE

DODDRIDGE 8.2K 227.2K LEWIS, RITCHIE

LEWIS 16.4K 243.6K WEBSTER, RITCHIE, GILMER

WEBSTER 9.2K 252.8K RITCHIE, GILMER

RITCHIE 10.4K 263.2K GILMER

GILMER 8.7K 271.9K WIRT, BRAXTON

WIRT 5.7K 277.6K CALHOUN, BRAXTON

CALHOUN 7.6K 285.2K ROANE, BRAXTON

ROANE 14.9K 300.1K BRAXTON

BRAXTON 14.5K 314.6K JACKSON, CLAY

CLAY 9.4K 324.0K NICHOLAS, JACKSON

NICHOLAS 26.2K 350.2K GREENBRIER, JACKSON

GREENBRIER35.5K 385.7K MONROE

MONROE 13.5K 399.2K SUMMERS, JACKSON, FAYETTE

FAYETTE 46.0K 445.2K SUMMERS

SUMMERS 13.9K 459.1K MERCER, JACKSON

MERCER 62.3K 521.4K MCDOWELL

MCDOWELL 22.1K 543.5K RALEIGH, JACKSON

RALEIGH 78.9K 621.4K

-------------------------- END DISTRICT TWO



Of course, District 3 would be the remaining counties. I went ahead and used the same algorithm on those counties for illustration purposes. Logan is the highest remaining county.



DISTRICT 3

COUNTY POPUL RUNNING POPULAITON SMALLEST REMAINING ADJACENCIES



LOGAN 36.7K 36.7K WYOMING

WYOMING 23.8K 59.5K BOONE, MINGO

BOONE 24.6K 84.1K MINGO

MINGO 26.8K 110.9K WAYNE

WAYNE 42.5K 153.1K LINCOLN, CABELL, KANAWHA

KANAWHA 193.1K 346.2K LINCOLN, JACKSON

JACKSON 29.2K 375.4K MASON, LINCOLN

MASON 27.3K 402.7K PUTNAM, CABELL, LINCOLN

CABELL 96.3K 499.0K PUTNAM, LINCOLN

PUTNAM 55.5K 554.4K LINCOLN

LINCOLN 21.7K 579.4K



The numbers don’t quite work out as I may have been working off two different sets of data. I had WV population as 1.853 million, with an ideal district size of 617.6 thousand. The county populations must have been from different data than the state population estimate.



If we ran the randomization again, we would end up with a completely different map. We could develop a system similar to this, with code that can be criticized by all and end up with a system to procedurally generate districts for the House of Representatives, the House of Delegates and the State Senate. We could broadcast the results so that the randomness is assured.



This is the resulting map from this experiment I ran:



http://i.imgur.com/ZyQBtIY.jpg



I would like to know your thoughts.



Reply · Report Post