Marion County Redistricting 2012: The Sequel

Whenever a political party realizes future (or current) demographic trends are not in its favor, aggressive redistricting is an inevitable result, presuming it has the foresight and skill to analyze such data. According to the Marion County Election Board voting results, in all of the last three elections, voting has been predominantly Democratic, which is typical of large cities in all states. In the 2010 election, straight party voting was 57% Democrat and 42% Republican. in the 2008 election, straight party voting was 63% Democrat and 37% Republican. President Obama won the vote with an even larger margin. Off-cycle election, like the 2010 and 2011 elections tend to be dominated by older voters, who lean conservative, therefore so do those elections, while voting in the presidential cycle tend to represent the broader population--which, in large cities, is strongly liberal. So the fact that since even our off-cycle elections have a 15% Democrat lead, means potential voting problems for the Republican Party in Marion County.

Currently, in the employ of Marion County, we have professional geographers and trained GIS specialists, who work on various mapping projects for us tax-payers, and have decades of experience with the nuances of Marion County geography, property lines, and political boundaries at all levels (school corporations, neighborhoods, townships, cities, tax districts, etc). However, last year, rather than tasking these specialists to independently create Marion County voting districts, the Mayor and Republican-dominated city council paid a Republican activist attorney to do both the reprecincting and redistricting, based on the new 2010 Census data, a legal obligation for the county to update its voting districts to fairly represent its populace. This attorney's qualifications for mapping is, and I quote, "I attended a seminar on redistricting." Unsurprisingly, the new precincts are highly problematic, crossing many existing legal boundaries, and having wide, and unreasonable variations in population. That assumes his data is correct. However, I have been unable to replicate his population statistics. Of the 600 precincts, my analysis indicates that 275 have different populations than what he published. One of the city-council requirements of new districts is that all of the district populations are with 3% of each other. According to the published population data, the new districts satisfy this requirement. However, according to my analysis, the districts vary by far more than this, with two districts having a population deviation of over 40% (proposed districts 14 and 16), with an average deviation of 20% (over 7,000 from a population ideal of about 36,000). If my analysis is correct, then not only are the new proposed districts technically inaccurate, but they are illegal, since they do not meet the requirement of new districts. The city-council and mayor were also warned by city GIS experts that there were problems with the new precincts, but those warnings were ignored. Subsequent to the publication of the new districts, the newly elected Democrat-dominant city-council has been working to commission an alternate redistricting, but the mayor is refusing to authorize any funds for the project. Last year the city paid over $250,000 for the project, with the money going to this Republican lawyer with no training in GIS or geography.

Table 1 Current Proposed New Districts (Brooks, 2011)
Proposed Districts (Brooks, 2011)	Population	%Black	%Hispanic	Dem	Rep	Partisan Difference
NEW-09	29,721	66%	3%	83%	13%	70%
NEW-07	39,942	47%	7%	77%	19%	58%
NEW-10	26,401	54%	22%	76%	20%	56%
NEW-13	38,201	64%	7%	76%	21%	55%
NEW-11	36,401	42%	9%	73%	21%	52%
NEW-14	36,843	57%	13%	73%	23%	50%
NEW-08	23,986	53%	8%	72%	24%	48%
NEW-17	33,536	43%	10%	68%	25%	43%
NEW-25	38,427	4%	4%	26%	66%	40%
NEW-20	37,113	3%	5%	30%	61%	31%
NEW-01	31,889	39%	15%	62%	32%	29%
NEW-24	27,787	3%	7%	31%	60%	29%
NEW-23	30,445	4%	7%	31%	60%	28%
NEW-06	38,211	30%	22%	56%	37%	19%
NEW-18	23,544	11%	6%	38%	53%	15%
NEW-22	31,164	11%	12%	38%	53%	15%
NEW-12	34,957	20%	11%	53%	38%	14%
NEW-05	27,415	15%	10%	41%	52%	11%
NEW-19	34,591	21%	7%	41%	51%	10%
NEW-16	31,967	11%	13%	42%	48%	6%
NEW-04	35,464	22%	7%	44%	50%	6%
NEW-03	35,228	20%	4%	44%	50%	5%
NEW-02	34,939	10%	6%	45%	48%	3%
NEW-15	40,321	26%	15%	48%	45%	3%
NEW-21	16,411	12%	9%	47%	45%	2%

In their effort to get alternative maps, the city-council worked with Common Cause to involve the public in the redistricting effort. Common Cause is a national organization whose goal is to maximize citizen participation in politics and organize non-partisan civic participation processes. For example, in matters of redistricting, they advocate for independent commissions to lead this process, rather than a Party. In support of this project, I created my own set of maps, with the goal of maximizing district competitiveness. I minimized other factors in my maps, like keeping intact communities of interest, compactness, and contiguity of districts. The latter terms represent attempts to minimize gerrymandering, by emphasizing that districts must "look reasonable"--i.e., rather than having meandering districts that are clearly designed to maximize partisan votes and exclude the minority party (or race), "nicely shaped" districts will ideally minimize these partisan shenanigans. However, several analysis of these factors indicate that they exacerbate problems rather than solve them. For example, by definition, once you enclose "communities of interest" into one district, you isolate them politically from their neighbors, and they will, more than likely, tend to vote similarly, producing highly partisan districts. Further, because of the natural clustering of communities of interest, the factors of compactness and contiguity can also produce the same effects. We see this in Indianapolis, in that the Democrat vote is clustered into an oval in lower northside, while the Republican vote is clustered in south Marion county and along the periphery. So while these three factors that are intended to subvert partisan gerrymandering have positive intent, they can create the same problems as intentional gerrymandering, but insidiously "look" like a neutral process. I argue that a more reasonable approach is to actively create competitive districts, which will then encourage politicians into political reasonableness as they hear from a diverse constituency, rather than forcing them to extreme positions when isolated constituencies have only themselves with whom to discuss political ideas.

MAP 1: VOTING PATTERNS (4 ELECTIONS AVERAGE, 2010-2011)

I have generated three maps and three tables. The first map (above) is simply a "heat map" of voting (based on an average of 4 elections from the last 2 years). The blue represents <40% Republican voting, while the red represents >60% Republican voting. Beige represents areas of political evenness, between 46-54% Republican voting. A similar map could be created to represent Democrat voting patterns, which looks almost identical. The first table (above) represents population and voting statistics of the districts created last year by the previous city-council (representing my analysis of the data, not the analysis that the attorney submitted to the council that accompanied his maps; ordered by least competitive). As can be seen, the new districts are 75% safe, with safety defined as one party having at least a 10% advantage over the opposing party. This is great for the favored party, who has to do little to win the district. For example, in many districts the minority party often chooses not to run a candidate, since there is no chance for a win, thus facilitating the establishment (or even the political requirement) of candidates who have extreme positions and may thus be unable to make any political compromises with the candidate in the neighboring district, creating legislative gridlock, none of which is in the public interest.

MAP 2: TOWNSLEY PROPOSED NEW DISTRICTS (COMPETITION OPTIMIZED)

Table 2 Townsley Proposed Districts #1: competitive Districts Optimized (2012)
Proposed Districts	Population	%Black	%Hispanic	%Dem	%Rep	Partisan Divide
D12	36592	69%	5%	82%	13%	69%
D11	36521	52%	6%	79%	16%	62%
D4	36837	53%	16%	74%	21%	53%
D13	36212	57%	15%	73%	22%	51%
D3	36565	47%	10%	69%	26%	43%
D25	35865	3%	3%	26%	66%	41%
D23	36870	3%	5%	28%	63%	35%
D10	36253	40%	22%	64%	30%	34%
D5	36246	23%	3%	61%	32%	29%
D24	36068	4%	8%	31%	60%	29%
D22	35862	5%	5%	32%	60%	29%
D2	35690	33%	13%	56%	38%	19%
D17	35763	21%	14%	54%	37%	18%
D19	36185	13%	6%	41%	50%	10%
D14	35823	20%	16%	43%	49%	6%
D18	35393	9%	8%	43%	49%	6%
D8	36812	24%	6%	44%	50%	6%
D9	36508	32%	5%	50%	44%	5%
D21	36549	31%	9%	49%	44%	5%
D7	35701	30%	7%	49%	45%	4%
D15	35529	17%	15%	47%	44%	3%
D16	35643	14%	12%	44%	46%	2%
D1	35654	24%	11%	47%	46%	1%
D20	35302	27%	8%	46%	47%	0%
D6	36659	15%	5%	46%	46%	0%

The second map represents a set of districts that maximizes political competitiveness. I have to admit that I am not happy with the districts. As can be seen in Table 2, over half of the districts are still safe for the dominant party. However, in contrast to the districts proposed last year, which have 9 districts with over 40% safety, my maps only have 6 districts with over 40% safety, and 12 districts that can be considered competitive (7 for the proposal from last year). While it is theoretically possible to make all 25 districts competitive, what would be sacrificed is the "reasonableness" of how the districts looked. I attempted to compromise between competitiveness and the "compactness/contiguity" standards. The third map represents a compromise based on existing school districts, attempting to minimize district boundary violations with school districts. As expected, the population deviations from ideal between districts are far larger than the first map, but I was able to maintain a relatively high number of competitive districts.

MAP 3: TOWNSLEY PROPOSED NEW DISTRICTS #2: SCHOOL DISTRICTS OPTIMIZED

Table 3 Townsley Proposed Districts #2: School Districts Optimized (2012)
Proposed District	Population	%Black	%Hispanic	%Dem	%Rep	Partisan Difference
D12	35930	24%	11%	84%	14%	70%
D11	35800	19%	7%	80%	17%	63%
D4	36219	51%	78%	76%	21%	55%
D13	35507	43%	15%	75%	23%	52%
D25	34183	53%	64%	27%	70%	43%
D3	36593	39%	25%	69%	26%	43%
D10	34365	29%	8%	67%	32%	35%
D23	37098	51%	10%	28%	63%	35%
D22	35627	25%	11%	32%	61%	29%
D24	36185	20%	21%	31%	60%	29%
D5	35786	43%	30%	62%	33%	29%
D2	38068	37%	53%	53%	35%	18%
D17	36713	4%	8%	53%	36%	17%
D19	32197	5%	6%	46%	57%	11%
D14	34616	3%	4%	45%	51%	6%
D18	38164	3%	7%	39%	45%	6%
D9	35123	21%	9%	52%	46%	6%
D21	35823	20%	25%	50%	45%	5%
D8	37907	33%	12%	43%	48%	5%
D7	34652	17%	7%	51%	47%	4%
D15	36382	9%	9%	46%	43%	3%
D16	37167	12%	17%	42%	44%	2%
D6	37364	20%	4%	46%	45%	1%
D1	39665	64%	5%	42%	42%	0%
D20	35968	15%	13%	46%	46%	0%