Applied Social Networks James Fowler University of California, San Diego Who is the Best Connected Legislator in the U.S.
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Applied Social Networks James Fowler University of California, San Diego Who is the Best Connected Legislator in the U.S. Congress? Who cares? Social connections have an important effect on political behavior and outcomes among voters influencing the flow of political information (Huckfeldt et al. 1995) voter turnout behavior (Fowler 2005; Highton 2000; Straits 1990) vote choice (Beck et al. 2002) Who is the Best Connected Legislator in the U.S. Congress? Social connections may also have an important effect on legislators well-connected legislators may be more influential with their peers better able to influence policy Methodological challenge: observability Social relationships are conducted in private Based on partisan, ideological, institutional, geographic, demographic, and personal affiliations. Recent large scale social network studies Hyperlink network between political interest groups Email networks Ebel, Mielsch, and Bornholdt 2002 Scientific collaboration networks Hindman, et al. 2003 Newman 2001 Network of committee assignments in the U.S. Congress Porter et al. 2005 Here: the network of legislative cosponsorships A directional link can be drawn from each cosponsor of a piece of legislation to its sponsor These links provide a rich source of information about the social network between legislators Cosponsorship and Social Connectedness Large literature analyzes which bills receive support individual motivations to cosponsor Mayhew 1974; Campbell 1982; Kessler and Krehbiel 1996; Koger 2003; Wilson and Young 1997; Panning 1982; Pellegrini and Grant 1999; Talbert and Potoski 2002 No literature considering which legislators receive support Yet several argue that bill sponsorship is a form of leadership Caldeira, Clark, and Patterson 1993; Hall 1992; Kessler and Krehbiel 1996; Krehbiel 1995; Schiller 1995 Cosponsorship and Social Connectedness Some argue that cosponsorships = “cheap talk” Kessler and Krehbiel 1996; Wilson and Young 1997 However, there may be substantial search cost involved in deciding which bills to cosponsor From 1973-2004 the average House member cosponsored only 3.4% of all proposed bills and the average Senator only cosponsored 2.4% Legislators expend considerable effort recruiting cosponsors and talking about them on the floor and with constituents (Campbell 1982) Oddly, only one published study of Cosponsorship networks Faust and Skvoretz (2002) interspecies comparison finds that Senate cosponsorship network most resembles the network of mutual licking between cows! Cosponsorship Data 280,000 “bills” proposed in the U.S. House and Senate from 1973 to 2004 (93rd-108th Congresses) recorded in Thomas over 2.1 million cosponsorship signatures partitioned by chamber and Congress to create 32 separate cosponsorship networks http://jhfowler.ucsd.edu/cosponsor.htm Cosponsorship in the House Congress House 93rd 94th 95th 96th 97th 98th 99th 100th 101st 102nd 103rd 104th 105th 106th 107th 108th Years 1973-1974 1975-1976 1977-1978 1979-1980 1981-1982 1983-1984 1985-1986 1987-1988 1989-1990 1991-1992 1993-1994 1995-1996 1997-1998 1999-2000 2001-2002 2003-2004 Mean Mean ÒBillsÓ ÒBillsÓ SponsoredCosponsored Mean Cosponsors per Total Total by Each by Each Cosponsors Mean SponsorsÒBillsÓLegislator Legislator per ÒBillÓ Legislator Distance 442 439 437 436 435 435 432 436 438 436 437 433 439 437 441 438 20994 19275 18578 10478 10062 9095 8606 8093 8423 8551 7464 6558 6780 7894 7541 7636 48 44 42 24 23 21 20 18 19 19 17 15 15 18 17 17 129 151 170 187 223 297 329 341 370 339 259 168 219 278 273 276 3 3 4 8 10 14 17 18 19 17 15 11 14 15 16 16 70 79 93 111 132 157 171 174 184 172 144 105 127 151 143 147 1.95 1.89 1.83 1.76 1.72 1.65 1.61 1.60 1.58 1.61 1.67 1.77 1.73 1.67 1.68 1.67 Cosponsorship in the Senate Congress Senate 93rd 94th 95th 96th 97th 98th 99th 100th 101st 102nd 103rd 104th 105th 106th 107th 108th Years 1973-1974 1975-1976 1977-1978 1979-1980 1981-1982 1983-1984 1985-1986 1987-1988 1989-1990 1991-1992 1993-1994 1995-1996 1997-1998 1999-2000 2001-2002 2003-2004 Mean Mean ÒBillsÓ ÒBillsÓ SponsoredCosponsored Mean Cosponsors per Total Total by Each by Each Cosponsors Mean SponsorsÒBillsÓLegislator Legislator per ÒBillÓ Legislator Distance 101 100 102 99 101 101 101 101 100 101 101 102 100 102 101 100 5123 4913 4722 4188 9674 11228 7596 7782 7370 7686 5824 8101 7001 8265 8745 7804 51 49 45 41 96 111 75 77 74 75 58 79 70 81 87 78 153 137 121 135 219 294 324 361 376 335 232 176 212 290 261 285 3 3 3 3 2 3 4 5 5 4 4 2 3 4 3 4 54 52 49 54 68 77 75 83 82 79 70 59 67 76 71 72 1.46 1.48 1.51 1.46 1.31 1.24 1.24 1.17 1.17 1.21 1.30 1.41 1.33 1.24 1.30 1.27 Mutual Cosponsorship Relations Congress 93rd 94th 95th 96th 97th 98th 99th 100th 101st 102nd 103rd 104th 105th 106th 107th 108th Any Bill House Senate 0.17 0.23 0.17 0.25 0.17 0.21 0.12 0.12 0.14 0.17 0.15 0.16 0.14 0.19 0.18 0.18 0.15 0.17 0.15 0.26 0.17 0.19 0.16 0.20 0.16 0.19 0.16 0.17 0.17 0.17 0.18 0.18 Total Number of Bills House Senate 0.23 0.39 0.20 0.34 0.19 0.33 0.15 0.26 0.22 0.27 0.23 0.36 0.21 0.34 0.25 0.39 0.24 0.39 0.14 0.30 0.23 0.34 0.21 0.29 0.24 0.36 0.25 0.37 0.29 0.47 0.34 0.43 Connectedness: An Alternative Measure Traditional measures of centrality generate plausible names None takes advantage of information about the strength of social relationships Total number of cosponsors on each bill Total number of bills sponsored by j and cosponsored by i Legislators recruit first those legislators to whom they are most closely connected. More cosponsors = lower probability of direct connection Bills with fewer total cosponsors more reliable Strength of the connection between i and j = 1/cij More bills in common = stronger relationship Weighted cosponsorship distance wij aij c Weighted cosponsorship distance Legislative connectedness Suppose direct distance from legislator j to legislator i is simple inverse of the cosponsorship weight Then use Dijkstra’s algorithm (Cormen et al. 2001) Starting with legislator j, identify from a list of all other legislators the closest legislator i Replace each of the distances with min dkj , dki dij Remove legislator i from the list and repeat until there are no more legislators on the list. Connectedness is the inverse of the average of these distances from all other legislators to legislator j. Results for the House Congress House 93rd 94th 95th 96th 97th 98th 99th 100th 101st 102nd 103rd 104th 105th 106th 107th 108th Best Connected Legislator 0.44 K och, Edward[D-NY-18] 0.57 P epper, Claude [D-FL-14] 0.60 P epper, Claude [D-FL-14] 0.31 P epper, Claude [D-FL-14] 0.27 Montgomery, G. [D-MS-3] 0.27 Roe, Robert A. [D-NJ-8] 0.26 Breaux, John [D-LA-7] 0.25 W axman, H enry A. [D-CA-29] 0.28 Stark, Fortney Pete [D-CA-9] 0.27 Fawell, H arris W. [R-IL-13] 0.22 W axman, H enry A. [D-CA-29] 0.24 Traficant, James [D-OH-17] 0.22 Gilman, Benjamin [R-NY- 20] 0.28 McCollum, Bill [R-FL-8] 0.24 Y oung, Don [R-AK] 0.28 Saxton, Jim [R-NJ-3] Strongest Sponsor/ CosponsorRelation Relationsh ip 69 72 51 58 29 30 16 57 23 14 8 7 7 10 11 14 Commerce Chair, RankingMember Armed Services Chair, Ranking Member Armed Services Chair, Ranking Member Armed Services Chair, Ranking Member Armed Services Chair, Ranking Member Armed Services Chair, Ranking Member Veterans Affairs Chair, Ranking Member Veterans Affairs Chair, Ranking Member ContiguousDistricts Courts and Intellectual P roperty Chair , Ranking Member Courts and Intellectual P roperty Chair , Ranking Member Courts and Intellectual P roperty Chair , Ranking Member ContiguousDistricts Transportation Chair, Ranking Member (Nearly) ContiguousDistricts, Repub. Study Committee House Administration Chair, Ranking Staggers, H arley [D-W V-2] / D evine, Samu el [R-OH-12] P rice, Melvin [D-IL-21] / Wilson, Robert [R-CA-41] P rice, Melvin [D-IL-21] / Wilson, Robert [R-CA-41] P rice, Melvin [D-IL-21] / Wilson, Robert [R-CA-41] P rice, Melvin [D-IL-21] / Dickinson, William [R-AL-2] P rice, Melvin [D-IL-21] / Dickinson, William [R-AL-2] Montgomery, G. [D-MS-3] / Hammerschmidt, J. [R-AR-3] Montgomery, G. [D-MS-3] / Solomon, Gerald [R-NY-24] Schulze, Richard T. [R-P A-5] / Yatron,Gus [D-P A-6] H ughes, William [D-NJ-2] / Moorhead, Carlos [R-CA-22] H ughes, William [D-NJ-2] / Moorhead, Carlos [R-CA-27] Moorhead, Carlos [R-CA-27] / Schroeder, Pat [D-CO-1] Ensign, John E. [R-NV-1] / Gibbons,Jim [R-NV-2] Shuster, Bud [R-P A-9] / O berstar, James L. [D-MN-8] DeMint, Jim [R-SC-4] / Myrick, Sue [R-NC-9] N ey, Robert W. [R-OH-18] / Larson, John B. [D-CT-1] Results for the Senate Congress Senate 93rd 94th 95th 96th 97th 98th 99th 100th 101st 102nd 103rd 104th 105th 106th 107th 108th Best Connected Legislator 0.94 Jackson,Henry [D-W A] 1.12 Moss, Frank [D-UT] 0.90 D ole, Robert J. [R-KS] 0.84 D ole, Robert J. [R-KS] 0.91 Heinz, H enry [R-P A] 1.28 Hatch, O rrin G. [R-UT] 1.37 Thurmond, Strom [R-SC] 1.46 Cranston, Alan [D-CA] 1.39 K ennedy, Edward M. [D-MA] 1.23 Mitchell, George J. [D-ME] 1.20 Mitchell, George J. [D-ME] 1.58 D ole, Robert J. [R-KS] 1.36 McCain, John [R-AZ] 1.36 Hatch, O rrin G. [R-UT] 1.61 Feingold, Russell D. [D-W I] 1.43 McCain, John [R-AZ] Strongest Sponsor/ CosponsorRelation 65 Magnuson,Warren [D-W A] / Cotton, Norris [R-NH] 139 Jackson,Henry [D-W A] / Fannin, P aul [R-AZ] 33 Inouye,Daniel [D-HI] / Matsunaga, Spark [D-HI] 24 Byrd, Robert [D-W V] / Baker, Howard [R-TN] 34 Inouye,Daniel [D-HI] / Matsunaga, Spark [D-HI] 63 Baker, H oward [R-TN] / Byrd, Robert [D-W V] 109 Cranston, Alan [D-CA] / W ilson,Pete [R-CA] 70 Byrd, Robert [D-W V] / D ole, Robert J. [R-KS] 77 Mitchell, George J. [D-ME] / Dole, Robert J. [R-KS] 179 Mitchell, George J. [D-ME] / Sasser, Jim [D-TN] 59 Mitchell, George J. [D-ME] / Dole, Robert J. [R-KS] 38 D ole, Robert J. [R-KS] / Daschle, Thomas A. [D-SD] 40 Lott, Trent [R-MS] / Daschle, Thomas A. [D-SD] 104 H utchison, K ay Bailey [R-TX] / Brownback, Sam [R-KS] 53 McCain, John [R-AZ] / Gramm, Phil [R-TX] 50 Frist, Bill [R-TN] / Daschle, Thomas A . [D-SD] Relationsh ip Commerce Chair, RankingMember Interiorand Insular Affairs Chair, RankingMember Same State Majority, Minority Leader Same State Majority, Minority Leader Same State Majority, Minority Leader Majority, Minority Leader Federal Housing Reform Majority, Minority Leader Majority, Minority Leader Majority, Minority Leader Marriage Penalty Relief and Bankruptcy Reform P ersonal Majority, Minority Leader Quality of Strongest Weighted Relationships Institutional Ties Regional Ties From the same state In the House they are often from contiguous districts Issue Ties House committee chairs and ranking members Senate majority and minority leaders Rep. Jim DeMint and Sue Myrick -- Republican Study Committee Sen. George Mitchell and Jim Sasser -- Federal Housing Reform Sen. Kay Bailey Hutchinson and Sam Brownback -- marriage penalty relief and bankruptcy reform Personal Ties Senator John McCain chaired Senator Phil Gramm’s 1996 Presidential campaign McCain has told the media that they have been friends since 1982 when they served together in the House (McGrory 1995) 108th House Top 20 108th Senate Top 20 External Validity: Legislative Influence Widely used measure of legislative influence is number of successful floor amendments Hall 1992; Sinclair 1989; Smith 1989; Weingast 1991 1 SD increase in connectedness increases successful floor amendments 53% in House 65% in Senate External Validity: Roll Call Votes Model roll call votes as in Poole and Rosenthal, adding connectedness score of sponsor 1 SD increase in connectedness of sponsor increases votes for bill by 5.2 in House 8.2 in Senate 2 SD increase would change 16% of House votes and 20% of Senate votes Landmark Legislation: An Alternative to Mayhew QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. Polarization in the 108th Senate QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. 108th House by Party QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. 108th House by Ideology QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. 108th House by State QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. 108th House by Committee QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. Polarization Over Time in the House QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. Polarization Over Time in the Senate QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture. Black Legislators in the 103rd House Black Legislators in the 104th House Black Legislators in the 108th House Poor Districts in the 108th House The Quantitative Judicial Literature Has focused on ideology of decisions and judges George and Epstein 1992; Segal 1985 “continues to present an underdeveloped theoretical and empirical understanding of why and when law changes” Hansford and Spriggs 2006 What if we could quantify the strength of a precedent’s importance? Questions We Might Answer How has the norm of stare decisis evolved over time? Does the Court consider the importance of a case when it decides whether or not to reverse it? Do reversed cases decline in importance once they are reversed? When the Court must reverse an important case, does it ground the reversing decision in important precedents? Which issues and cases does the Court prioritize? How do these priorities change over time? Quantifying Precedent Each judicial citation is a latent judgment about the cases cited (and not cited) When justices write opinions, they spend time researching the law and selecting precedents to support their arguments We can utilize the quantity and quality of judicial citations to measure the importance of a precedent Past Attempts to Quantify Precedent Measurements of the prestige of judges (Kosma 1998; Landes, Lessig, and Solimine 1998) Citation behavior of appellate courts (Caldeira 1985; Harris 1985) Role of legal rules in specific issue domain (Landes and Posner 1976; McGuire 2001; Ulmer 1970) Past Attempts to Quantify Precedent Large scale network analysis (Chandler 2005; Smith 2005) Legal vitality (Hansford and Spriggs 2006) None consider quality of citations dynamics of legal change Data Collection Generate List of Supreme Court “Decisions” Shepard’s citations to Supreme Court decisions from Other Supreme Court decisions Appellate courts District courts State courts Law journals Other secondary sources Majority, concurring, dissenting opinions Data Collection Shepard’s data includes types of citations String cite or treatment Positive or negative Will (eventually) help distinguish between Salience (string-cite network) Authority (treatment network) Types of Citations A cited case may be Regardless of content, each citation is a latent judgment about which cases are most important an important ruling salient to the citing case a reversed opinion an overruled case like Plessy v. Ferguson (1896) is probably more important than an overruled case like Crain v. United States (1896) Thus, we include all judicial citations in our analysis Extended Network of Abortion Decisions Mean Inward & Outward Citations by Year Citations and Stare Decisis Prior to 19th century, both inward and outward citations rare Outward citations slowly rise in the 19th century norm takes hold number of previous cases that could potentially be cited increases Inward citations also rise during this period there was no “firm doctrine of stare decisis” (Kempin 1959, 50) justices begin writing more broadly applicable legal rules Inward citations fall in recent years Citations and Stare Decisis Goodhart (1930) argues that by 1900, the doctrine of stare decisis was in full effect Inward and outward citations continued to rise in the 20th century To what extent does this rise signify a further strengthening of the norm? How many cases cite at least one other case? 40 60 80 stare decisis in full effect 20 Warren Court 0 Cases With At Least One Outward Citation (%) 100 Percentage of Cases with At Least One Outward Citation by Year 1750 1800 1850 1900 Year 1950 2000 Stare Decisis and the Warren Court Warren Court (1953-1969) departs from stare decisis Consistent with argument Warren Court was “activist” Sharp decrease in outward citiations Sharp decrease in cases that do not cite any precedents overruled more precedents than any other Court (Brenner and Spaeth 1995) revolutionized Constitutional law (Horwitz 1998; Powe 2000; Schwartz 1996) Warren Court also experiences sharp drop in inward citations Surprising, given Burger (1969-1986) and Rehnquist (1986-2005) Courts cases contain highest outward citations in history Possible Explanations Weak legal basis of Warren Court precedents “Warren Court decisions did not articulate specific doctrinal analyses, and therefore did not provide firm guidance for future Courts” (Strossen 1996, 72). Subsequent Courts would have trouble following Warren Court’s “many ambiguities, loopholes, and loosely formulated rules” (Emerson 1980, 440). Justices as policy oriented actors More conservative Burger and Rehnquist Courts unable to justify policy choices with liberal Warren Court precedents Forced to cite their own or pre-Warren precedents Which Precedents Are Most Important? Expert opinions identify “landmark” cases in the Supreme Court’s history Congressional Quarterly’s Guide to the United States Supreme Court (1997) – 2,500 cases Oxford Guide to Supreme Court Decisions (1999) – 440 cases Represents small fraction of 28,951 majority opinions that have been written by the Court Why rely on third parties when the citation network contains the evaluations of the justices themselves? Importance in Selected Landmark Abortion Decisions Network AUHTORITY HUB Importance Ranks of Selected Landmark Abortion Decisions Outward Citations Inward Importance % Rank Outward Importance % Rank Inward Citations Outward Citations 4 0 1.00 0.03 72 0 .997 1.0 90 88 Akron v. Akron Center for Reproductive Health, 462 U.S. 416 (1983) 0.80 0.40 3 1 0.89 0.96 9 15 0.941 0.986 22 28 0.60 2 2 0.75 0.81 3 10 0.845 0.986 7 52 Webster v. Reproductive Health Services, 492 U.S. 490 (1989) 0.40 0.80 1 3 0.68 0.97 3 16 0.911 0.985 7 63 Planned Parenthood of Southeastern Pennsylvania v. Casey, 505 U.S. 833 (1992) 0.20 1.00 0 4 0.67 1.00 6 21 0.957 0.997 18 89 Thornburgh v. American College, 476 U.S. 747 (1986) 0.60 Inward Importance % Rank 1.00 0.20 Inward Importance % Rank Decision Roe v. Wade, 410 U.S. 113 (1973) Inward Citations Complete Network Outward Citations Outward Importance % Rank 72 Case Network Inward Citations Outward Importance % Rank 5 Case Network Checking the Results Akron has fewer outward citations than Webster, but higher outward importance Means Akron cites cases that are more important Portion of cited cases considered important by Oxford Guide or CQ 82% (23/28) of Akron’s 67% (35/52) of Webster’s Top 20 Inward Important Cases in 2005 Case Cantwell v. Connecticut (1940) Schneider v. State (Town of Irvington) (1930) New York Times v. Sullivan (1964) Thornhill v. Alabama (1940) NAACP v. Button (1963) NAACP v. Alabama Lovell v. City of Griffin (1938) Chaplinsky v. New Hampshire (1942) McCulloch v. Maryland (1819) Shelton v. Tucker (1960) Stromberg v. California (1931) Roth v. U.S. (1957) Near v. Minnesota (1931) Speiser v. Randall (1958) Thomas v. Collins (1945) Hague v. Committee for Industrial Org. (1951) Buckley v. Valeo (1976) Pierce v. Society of Sisters (1925) DeJonge v. Oregon (1937) Whitney v. California (1927) Inward Importance Score (Percentile Rank) 0.1983 (1.000000) 0.1648 (.9999654) 0.1567 (.9999309) 0.1475 (.9998963) 0.1473 (.9998618) 0.1415 (.9998273) 0.1348 (.9997928) 0.1158 (.9997582) 0.1130 (.9997237) 0.1064 (.9996891) 0.1047 (.9996546) 0.1046 (.9996200) 0.1038 (.9995855) 0.1030 (.9995509) 0.1022 (.9995164) 0.1015 (.9994819) 0.1012 (.9994473) 0.1007 (.9994128) 0.0936 (.9993783) 0.0892 (.9993437) Top 20 Outward Important Cases in 2005 Case First National Bank v. Bellotti (1978) Griswold v. Connecticut (1965) Buckley v. Valeo (1976) Dennis v. U.S. (1951) Young v. American Mini Theatres Inc. (1976) Grayned v. City of Rockford (1972) Kovacs v. Cooper (1949) Gibson v. FL Legislative Investigation Committee (1963) Communist Party of U.S. v. Subversive Activities Control Board (1961) Members of City Council of L.A. v. Taxpayers for Vincent (1984) VA State Board of Pharmacy v. VA Citizens Consumer Council (1976) Roe v. Wade (1973) American Communications Assn. v. Douds (1950) Richmond Newspapers Inc. v. VA (1980) Consol. Edison Co. of NY v. Public Service Commission of NY (1980) NAACP v. Claiborne Hardware Co. (1982) New York v. Ferber (1982) Metromedia v. City of San Diego (1981) New York Times. V. Sullivan (1964) R.A.V. v. City of St. Paul (1992) Outward Importance Score (Percentile Rank) 0.1291 (1.000000) 0.1159 (.9999654) 0.1157 (.9999309) 0.1079 (.9998963) 0.1073 (.9998618) 0.1007 (.9998273) 0.0899 (.9997928) 0.0936 (.9997582) 0.0932 (.9997237) 0.0920 (.9996891) 0.0917 (.9996546) 0.0893 (.9996200) 0.0888 (.9995855) 0.0861 (.9995509) 0.0855 (.9995164) 0.0848 (.9994819) 0.0837 (.9994473) 0.0814 (.9994128) 0.0796 (.9993783) 0.0786 (.9993437) Speiser v. Randall (1958) Considered by ACLU one of the 100 most important Supreme Court decisions Excluded from 1979 first edition of Congressional Quarterly’s Guide to the U.S. Supreme Court Partitioning network to 1979 puts Speiser in top 20 It has taken judicial specialists 18 years with the publication of the 1997 third edition of the Guide, to recognize the significance of Speiser Validity How well do importance measures measure importance? Important cases should be cited more often than other cases Regress count of citations to each case by year on importance measures (negative binomial) Include lagged dependent variable, age variables, and adjust for clustering Relationship Between Importance Measures and Future Citations of U.S. Supreme Court Precedent by the U.S. Supreme Court, 1792-2005 Inward Eigenvector Centrality Outward Eigenvector Centrality New York Times Amici Briefs CQ List Oxford List 3.32 (0.03) 2.76 0.065 0.041 (0.04) (0.001) (0.001) 2.06 (0.03) 2.22 (0.04) 0.61 (0.03) 0.16 (0.01) 1.30 (0.03) 1.75 (0.05) 0.36 (0.01) 0.55 (0.01) 0.44 (0.01) 0.63 (0.01) 0.74 (0.01) 0.68 (0.01) 0.43 (0.01) 0.46 (0.01) 0.68 (0.01) 0.73 (0.01) -0.84 (0.01) -0.41 (0.01) -0.47 (0.01) -0.32 (0.01) -0.43 (0.01) -0.24 (0.01) -0.08 (0.01) -0.07 (0.01) -0.32 (0.01) -0.31 (0.01) Age -0.004 -0.009 -0.022 -0.014 (0.001) (0.001) (0.001) (0.001) -0.023 (0.001) -0.007 (0.001) -0.039 -0.040 -0.016 -0.018 (0.002) (0.002) (0.001) (0.001) Constant -1.84 (0.01) -2.81 (0.03) -0.86 (0.01) -1.44 (0.02) -1.47 (0.01) -3.03 (0.04) -0.72 (0.02) -0.70 (0.02) -1.18 (0.01) -1.11 (0.01) Dispersion 1.48 (0.02) 1.47 (0.03) 1.78 (0.04) 1.90 (0.04) 2.18 (0.03) 1.81 (0.03) 1.34 (0.03) 1.42 (0.03) 1.92 (0.03) 2.08 (0.03) Outward Cites Outward Importance Importance Measure Lagged Dep. Variable Ln(Age) Inward Cites Importance Measure: Inward Importance Dependent Variable: Number of Times a U.S. Supreme Court Case is Cited by the U.S. Supreme Court in the Following Year -571443 -584038 -579838 -599022 -603595 Log PseudoLikelihood Null Likelihood -710668 -710668 -710668 -710668 -710668 2485411 2485411 2485411 2485411 2485411 N -600182 -128951 -129611 -600991 -606027 -710668 -142503 -142503 -707601 -708910 2485411 198884 198884 2482076 2483569 Relationship Between Importance Measures and Future Citations of U.S. Supreme Court Precedent by U.S. Courts of Appeals, 1792-2005 Inward Eigenvector Centrality Outward Eigenvector Centrality New York Times Amici Briefs CQ List Oxford List 2.14 (0.03) 1.85 0.064 0.046 (0.03) (0.001) (0.001) 1.12 (0.03) 2.25 (0.04) 0.27 (0.02) 0.06 (0.01) 1.04 (0.03) 1.29 (0.05) 0.28 (0.01) 0.30 (0.01) 0.26 (0.01) 0.29 (0.01) 0.37 (0.01) 0.29 (0.01) 0.10 (0.00) 0.10 (0.00) 0.34 (0.01) 0.35 (0.01) -0.45 (0.01) -0.19 (0.01) -0.26 (0.01) -0.14 (0.01) -0.17 (0.01) -0.05 (0.01) -0.05 (0.01) -0.04 (0.01) -0.11 (0.01) -0.09 (0.01) Age -0.009 -0.011 -0.02 -0.014 (0.001) (0.001) (0.001) (0.001) -0.019 (0.001) -0.007 (0.001) -0.023 -0.023 -0.016 -0.017 (0.001) (0.001) (0.001) (0.001) Constant -0.93 (0.02) -1.63 (0.03) -0.36 (0.02) -0.92 (0.02) -0.82 (0.02) -2.50 (0.04) 0.92 (0.03) 0.94 (0.03) -0.69 (0.02) -0.65 (0.02) Dispersion 2.49 (0.02) 2.53 (0.05) 2.43 (0.04) 2.59 (0.05) 2.97 (0.06) 2.45 (0.05) 1.12 (0.04) 1.13 (0.04) 2.75 (0.05) 2.87 (0.05) -1455994 -1469643 -1449509 -1474305 -1495797 -1468278 -418495 -418922 -1476027 -1488338 -1829049 -1829049 -1829049 -1829049 -1829049 -1829049 -481819 -481819 -1809860 -1817550 2485411 2485411 2485411 2485411 2485411 2485411 198884 Log PseudoLikelihood Null Likelihood N Outward Cites Outward Importance Importance Measure Lagged Dep. Variable Ln(Age) Inward Cites Importance Measure: Inward Importance Dependent Variable: Number of Times a U.S. Supreme Court Case is Cited by the U.S. Court of Appeals in the Following Year 198884 2482076 2483569 Relationship Between Importance Measures and Future Citations of U.S. Supreme Court Precedent by State Courts, 1792-2005 Inward Eigenvector Centrality Outward Eigenvector Centrality New York Times Amici Briefs CQ List Oxford List 2.54 (0.03) 1.98 0.065 0.039 (0.05) (0.001) (0.001) 1.80 (0.03) 1.58 (0.04) 0.37 (0.03) 0.74 (0.01) 1.05 (0.03) 1.41 (0.06) 0.23 (0.01) 0.26 (0.01) 0.22 (0.01) 0.29 (0.01) 0.33 (0.01) 0.29 (0.01) 0.11 (0.00) 0.12 (0.00) 0.30 (0.01) 0.32 (0.01) -0.42 (0.01) -0.09 (0.01) -0.17 (0.01) -0.02 (0.01) -0.14 (0.01) 0.04 (0.01) -0.03 (0.01) -0.03 (0.01) -0.01 (0.01) 0.00 (0.01) Age -0.009 -0.011 -0.020 -0.015 (0.001) (0.001) (0.000) (0.001) -0.022 (0.001) -0.011 (0.001) -0.019 -0.018 -0.017 -0.018 (0.001) (0.001) (0.000) (0.000) Constant -1.19 (0.01) -1.92 (0.03) -0.50 (0.02) -1.07 (0.02) -1.06 (0.02) -2.12 (0.04) 0.46 (0.03) 0.48 (0.03) -0.84 (0.02) -0.79 (0.02) Dispersion 2.09 (0.04) 2.28 (0.05) 2.21 (0.04) 2.54 (0.05) 2.68 (0.05) 2.55 (0.05) 1.66 (0.04) 1.68 (0.04) 2.62 (0.05) 2.71 (0.05) -1521236 -1550635 -1533143 -1571520 -1571000 -1574734 -371327 -371981 -1571423 -1580042 -1931174 -1931174 -1931174 -1931174 -1931174 -1931174 -430155 -430155 -1918232 -1923021 2485411 2485411 2485411 2485411 2485411 2485411 198884 Log PseudoLikelihood Null Likelihood N Outward Cites Outward Importance Importance Measure Lagged Dep. Variable Ln(Age) Inward Cites Importance Measure: Inward Importance Dependent Variable: Number of Times a U.S. Supreme Court Case is Cited by State Courts in the Following Year 198884 2482076 2483569 Comparison of Alternative Importance Measures for Predicting Future Citations to U.S. Supreme Court Precedent by the U.S. Supreme Court, 1792-2005 Effect Size: Percent Increase in Probability a U.S. Supreme Court Case is Cited by the U.S. Supreme Court in the Following Year Given a One Standard Deviation Change in the Importance Measure New York Times Amici Briefs CQ List Oxford List Log Likelihood Ratio N Outward Eigenvector Centrality Alternative Importance Measure Inward Eigenvector Centrality Outward Importance Outward Cites Inward Importance Inward Cites Alternative Importance Measure: 73.8 (0.8) 35.7 (0.9) 33.1 (0.8) 23707 103.6 (0.5) 32.6 (1.6) 10.4 (0.5) 33953 101.0 (1.4) 46.1 (1.6) 4.1 (0.9) 37219 106.2 (1.3) 38.0 (1.9) 8.4 (1.1) 33887 56.9 (1.2) 60.0 (1.8) 9.5 (0.9) 5624 59.6 (1.2) 61.2 (1.9) 6.7 (0.9) 6191 97.6 (1.2) 39.2 (1.6) 12.0 (0.5) 39694 99.9 (1.1) 42.0 (1.4) 11.1 (0.5) 44041 2485411 2485411 2485411 2485411 198884 198884 2482076 2483569 Comparison of Alternative Importance Measures for Predicting Future Citations to U.S. Supreme Court Precedent by U.S. Appeals Courts, 1792-2005 Effect Size: Percent Increase in Probability a U.S. Supreme Court Case is Cited by the U.S. Courts of Appeals in the Following Year Given a One Standard Deviation Change in the Importance Measure New York Times Amici Briefs CQ List Oxford List Log Likelihood Ratio N Outward Eigenvector Centrality Alternative Importance Measure Inward Eigenvector Centrality Outward Importance Outward Cites Inward Importance Inward Cites Alternative Importance Measure: 29.9 (1.0) 21.7 (1.0) 39.2 (1.2) 14023 58.2 (1.1) 10.9 (1.3) 21.7 (0.9) 29127 84.0 (1.3) 25.1 (1.1) -23.3 (1.2) 48387 66.1 (1.1) -5.5 (1.4) 62.6 (1.4) 27704 34.9 (1.6) 32.0 (1.9) -1.1 (0.9) 8886 34.6 (1.5) 31.8 (1.9) -0.7 (0.9) 9308 55.1 (1.0) 25.3 (1.1) 9.3 (0.5) 41662 56.9 (1.0) 27.0 (1.1) 7.0 (0.6) 47487 2485411 2485411 2485411 2485411 198884 198884 2482076 2483569 Comparison of Alternative Importance Measures for Predicting Future Citations to U.S. Supreme Court Precedent by the U.S. District Court, 1792-2005 Effect Size: Percent Increase in Probability a U.S. Supreme Court Case is Cited by the State Courts in the Following Year Given a One Standard Deviation Change in the Importance Measure 79.9 (1.2) 18.0 (1.5) 9.3 (0.6) 417027 83.7 (1.5) 25.6 (1.4) -2.8 (1.3) 415492 80.9 (1.2) 24.2 (1.7) 2.3 (1.3) 415470 56.0 (1.9) 66.1 (2.9) -1.0 (1.0) 74008 56.0 (1.9) 66.6 (2.9) -2.6 (1.3) 74030 76.8 77.3 (1.1) (1.1) 23.1 24.9 (1.4) (1.3) 9.7 8.7 (0.6) (0.7) 414892 415891 2485411 2485411 2485411 2485411 198884 198884 2482076 2483569 Oxford List Amici Briefs 53.3 (1.1) 20.7 (1.2) 29.6 (0.9) 428613 CQ List New York Times Log Likelihood Ratio N Outward Eigenvector Centrality Alternative Importance Measure Inward Eigenvector Centrality Outward Importance Outward Cites Inward Importance Inward Cites Alternative Importance Measure: The Dynamics of a Precedent’s Importance Expert evaluations give us a static picture of the present Importance scores can give us a dynamic picture Partition the network by terminal year (1792-1800, 1792-1801, etc.) Find importance scores for each partition Permits observation of how importance of each decision changes through time Rise of Brown and Roe Rise of Brown and Roe Rise of Brown and Roe Brown legally weak when first issued (Baum 1985; Epstein and Walker 2004; Johnson and Cannon 1984; O’Brien 2003) “the judiciary itself was ambivalent about the [Brown] policy… the original Brown opinion [revealed] little judicial commitment to a philosophy of racial equality” (Johnson and Cannon 1984) barely more than 1% of schools desegregated by 1964 Roe was immediately effective, voiding laws in every state that prohibited or limited abortion (Segal and Spaeth 1996) 181,140 abortions in the first three months after Roe—more than 8 times the number in all of 1969 (Rosenberg 1991; Bond and Johnson 1982) Changes in Court Priorities Once important decisions decline substantially from their peaks as legal rules settle beyond controversy Bank of Augusta v. Earle (1839), Gibbons v. Ogden (1824), and Minnesota Rate Cases (1913) Changes in importance reflect (in part) changes in types of issues Court chooses to address “[F]or the first 150 years of its history, the Supreme Court exerted its greatest influence on the states of the Union through its decisions on matters of economic interest. In case after case—as the justices construed the contract clause, the commerce clause, and defined the state’s power of taxation—the Court determined the relationship of state to federal power” (Biskupic and Witt 1997) The Rise and Fall of Importance QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. Changing Importance of Commerce and Civil Rights Issues QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. Fifth Amendment Cases QuickTime™ and a TIFF (LZW) decompressor are needed to see this picture. Placement Scores vs. USNWR