In the United States District Court for the District of Marland Greenbelt Division
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Case 8:11-cv-03220-RWT Document 43-16 Filed 12/07/11 Page 1 of 53 IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF MARLAND GREENBELT DIVISION MS.PATRICIA FLETCHER, ) et al., ) ) Civ. Action No.: RWT-11-3220 ) Plaintiffs, ) ) v. ) ) LINDA LAMONE in her official ) capacity as State Administrator of ) Elections for the state of Maryland; ) And ROBERT L. WALKER in his ) official capacity as Chairman of the ) State Board of Elections, ) ) Defendants. ) _____________________________________) DECLARATION AND EXPERT REPORT OF RONALD KEITH GADDIE, Ph.D. Case 8:11-cv-03220-RWT Document 43-16 Filed 12/07/11 Page 2 of 53 DECLARATION OF RONALD KEITH GADDIE I, Ronald Keith Gaddie, being competent to testify, hereby affirm on my personal knowledge as follows: 1. My name is Ronald Keith Gaddie. I reside at 3801 Chamberlyne Way, Norman, Oklahoma, 73072. I have been retained as an expert to provide analysis of the Maryland congressional districts by counsel for the Fannie Lou Hamer Coalition. I am being compensated at a rate of $300.00 per hour. I am a tenured professor of political science at the University of Oklahoma. I teach courses on electoral politics, research methods, and southern politics at the undergraduate and graduate level. I am also the general editor (with Kelly Damphousse) of the journal Social Science Quarterly. I am the author or coauthor of several books, journal articles, law review articles, and book chapters and papers on aspects of elections, including most recently The Triumph of Voting Rights in the South. In the last decade I have worked on redistricting cases in several states, and I provided previous expert testimony on voting rights, redistricting, and statistical issues. I have also testified in trials or provided expertise to defendants, plaintiffs, intervenors, and jurisdictions in California, Florida, Georgia, Illinois, Louisiana, New Mexico, New York, Oklahoma, South Dakota, Texas, Virginia, Wisconsin, and Wyoming, and appeared as an expert witness before committees of the U.S. House, the U.S. Senate, and the U.S. Commission on Civil Rights. A complete list of my cases and retentions appears along with my academic background and list of publications in my attached vita (Exhibit A). 2. This report describes (1) the compactness of districts in the recently-adopted Maryland congressional district map and plaintiff’s map; (2) levels of voter turnout by racial and ethnic group for 2002-2010; and (3) racial polarization in Maryland elections featuring black versus white candidates. I also offer some response to the November 30, 2011 report of Professor Bruce Cain. 3. In preparing this report, I have relied on demographic data from the 2010 US Census and elections data for the state of Maryland. Election and demographic data used for this report were provided by counsel and prepared by Magellan Strategies. Unless otherwise indicated, all data analyses are generated at my direction or run on SPSS release 18.0 and Ei. 4. COMPACTNESS: 4.1 Traditional redistricting principles hold that more compact districts are preferable to less- compact districts, because more-compact districts are related to higher levels of participation and increase the ability of candidates to contact voters,1 which increases efficacy and contributes to 1Richard N. Engstrom (2000). “Electoral District Compactness and Voters.” American Review of Politics 21: 383 - 396. Case 8:11-cv-03220-RWT Document 43-16 Filed 12/07/11 Page 3 of 53 the health of representative Democracy.2 The courts observed that redistricting is an activity where looks matter – and ‘looks’ refers to compactness.3 4.2 A variety of statistical measures have evolved to measure compactness, though they usually reduce down to two: indicators of circular shape, and indicators of circular filling.4 The two most widely used measures of compactness applied to districts are the Perimeter-to-Area measure and the Smallest Circle score. These measures were regularly offered in post-Shaw litigation of the 1990s. And, traditionally, districting plans are assessed in the context of total (average) plan compactness, though the compactness of individual districts is advanced when attempting to lend context to the design of particular districts (illustrations of both measures are in Figure 1.) The Perimeter-to-Area (PTA) measure compares the relative length of the perimeter of a district to its area. It represents the area of the district as the proportion of the area of a circle with the same perimeter. The score ranges from 0 to 1, with a value of 1 indicating perfect compactness. This score is achieved if a district is a circle. Most redistricting software generates this measure as the Polsby-Popper statistic. Smallest Circle (SC) scores measure the space occupied by the district as a proportion of the space of the smallest encompassing circle, with values ranging from 0 to 1. A value of 1 indicates perfect compactness and is achieved if a district is a circle. This statistic is often termed the Reock measure by redistricting applications.5 4.3 Computed compactness scores for the plan used during the last decade (‘baseline’ or plan used from 2002 through 2010), the governor’s initial plan (GRAC), the recently adopted plan (SB-1), and the Fannie Lou Hamer Coalition plaintiff’s plan (FLHC) appear in Table 1. 4.4 The FLHC map is more compact than the state’s baseline map or SB-1 on both conventional measures, the perimeter-to-area score (PTA) and the smallest circumscribing circle (SC) and it is these measures that are included in this report. 4.5 The state map, SB-1, has the same average SC score, as the baseline map (.27 in both), but reduces the PTA score from .14 to .11 (making it less compact). The perimeter to area score is more sensitive to irregularities of district shape – especially concave shapes that ‘core out’ portions of a district -- and they are also sensitive to the relative smoothness of district lines. 2See, for example, Peter Weilhouwer and Brad Lockerbie, 1994. “Party Contacting and Political Participation.” American Journal of Political Science 38: 211-229. 3 See Justice Sandra Day O’Connor’s opinion in Shaw v. Reno, 509 U.S. 630 (1993). 4Richard G. Niemi, Bernard Grofman, Carl Carlucci, and Thomas Hofeller. 1990. “Measuring Compactness and the Role of Compactness Standard in a Test for Partisan and Racial Gerrymandering.” Journal of Politics 52: 1155-1181; see also H. P. Young. 1988. “Measuring the Compactness of Legislative Districts.” Legislative Studies Quarterly 13: 105-115. 5Ernest C. Reock, Jr. 1961. “A Note: Measuring Compactness as a Requirement of Legislative Apportionment.” Midwest Journal of Political Science 5: 70-74. Case 8:11-cv-03220-RWT Document 43-16 Filed 12/07/11 Page 4 of 53 Adding a small amount to the perimeter of a district while capturing the same area within the district can substantially lower its perimeter score while leaving the smallest circle score unchanged. Suppose we had a district with a 100 square mile area, 20 miles long, 5 miles wide, with a 50 mile perimeter and a 20.615 mile longest axis. If we were to maintain the long axis of the district and also keep the internal area of the district constant, but manipulate the shape of the district, the perimeter grows longer and, consequently, the size of the comparative circle of the same perimeter grows much larger. Figures 2 and 3 illustrates this phenomenon: District A has a perimeter of 50 miles and an area of 100 square miles. The area of the smallest circumscribing circle is 333.714 square miles; the area of the circle with the same perimeter (50 miles) is 198.981 square miles. The rectangular district that has a SC score of 100/333.714 = .30. The PTA score is 100/198.981 = .503. In District B, we keep the same area (100 square miles) and the same longest axis (20.615 miles), but manipulate the district boundary to add 14.14 miles of perimeter. The SC score remains unchanged, .30. But, change is afoot in the perimeter-to-area score. The perimeter of the comparative circle for the perimeter-to-area score has grown by 28%, and the area of the comparative circle grows from 198.981 miles to 327.440 miles, an increase of 65% in the denominator for the PTA score. The PTA drops to .305. In District C, we again keep the same area (100 square miles) and the same longest axis (20.615 miles), but manipulates the district boundary to add 47.44 miles of perimeter compared to District A. Again, the SC score remains unchanged, .30. But the perimeter of the comparative circle for the PTA score is 92% larger than for District A, and the area of the comparative circle grows from 198.981 square miles to 755.695 square miles, a 279.7% increase in the denominator for the PTA score. The PTA drops to .132. The lowest PTA score in SB-1 is .03, which means that if you crafted a circle of the same perimeter and measured the area within the circle, district 3 would occupy just 3% of the area. Six districts in the SB-1 plan score less than .1 with District 2 scoring .06, Districts 6 and 8 score .08 and Districts 4 and 7 score at .09 on the PTA measure. The area within these districts is equal to less than a tenth of the area of a circle of identical perimeter. 4.6 If we compare the most compact majority-minority district in the state map (District 7, with a PTA of .09 and a SC of .36), it is less compact than the most compact majority-minority district in the FLHC map (District 7, PTA = .47, SC = .64).