applied social networks

AppliedSocial Networks

James FowlerUniversity 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

Hindman, et al. 2003 Email networks

Ebel, Mielsch, and Bornholdt 2002 Scientific collaboration networks

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/cosponsorship.htm

http://jhfowler.ucsd.edu/cosponsorship.htm

Cosponsorship in the House

Congress Years Total

Sponsors Total

“Bills”

Mean “Bills”

Sponsored by Each

Legislator

Mean “Bills”

Cosponsored by Each

Legislator

Mean Cosponsors per “Bill”

Cosponsors per

Legislator Mean

Distance House 93rd 1973-1974 442 20994 48 129 3 70 1.95 94th 1975-1976 439 19275 44 151 3 79 1.89 95th 1977-1978 437 18578 42 170 4 93 1.83 96th 1979-1980 436 10478 24 187 8 111 1.76 97th 1981-1982 435 10062 23 223 10 132 1.72 98th 1983-1984 435 9095 21 297 14 157 1.65 99th 1985-1986 432 8606 20 329 17 171 1.61 100th 1987-1988 436 8093 18 341 18 174 1.60 101st 1989-1990 438 8423 19 370 19 184 1.58 102nd 1991-1992 436 8551 19 339 17 172 1.61 103rd 1993-1994 437 7464 17 259 15 144 1.67 104th 1995-1996 433 6558 15 168 11 105 1.77 105th 1997-1998 439 6780 15 219 14 127 1.73 106th 1999-2000 437 7894 18 278 15 151 1.67 107th 2001-2002 441 7541 17 273 16 143 1.68 108th 2003-2004 438 7636 17 276 16 147 1.67

Cosponsorship in the Senate

Congress Years Total

Sponsors Total

“Bills”

Mean “Bills”

Sponsored by Each

Legislator

Mean “Bills”

Cosponsored by Each

Legislator

Mean Cosponsors per “Bill”

Cosponsors per

Legislator Mean

Distance Senate

93rd 1973-1974 101 5123 51 153 3 54 1.46 94th 1975-1976 100 4913 49 137 3 52 1.48 95th 1977-1978 102 4722 45 121 3 49 1.51 96th 1979-1980 99 4188 41 135 3 54 1.46 97th 1981-1982 101 9674 96 219 2 68 1.31 98th 1983-1984 101 11228 111 294 3 77 1.24 99th 1985-1986 101 7596 75 324 4 75 1.24 100th 1987-1988 101 7782 77 361 5 83 1.17 101st 1989-1990 100 7370 74 376 5 82 1.17 102nd 1991-1992 101 7686 75 335 4 79 1.21 103rd 1993-1994 101 5824 58 232 4 70 1.30 104th 1995-1996 102 8101 79 176 2 59 1.41 105th 1997-1998 100 7001 70 212 3 67 1.33 106th 1999-2000 102 8265 81 290 4 76 1.24 107th 2001-2002 101 8745 87 261 3 71 1.30 108th 2003-2004 100 7804 78 285 4 72 1.27

Mutual Cosponsorship Relations Any Bill Total Number of Bills

Congress House Senate House Senate 93rd 0.17 0.23 0.23 0.39 94th 0.17 0.25 0.20 0.34 95th 0.17 0.21 0.19 0.33 96th 0.12 0.12 0.15 0.26 97th 0.14 0.17 0.22 0.27 98th 0.15 0.16 0.23 0.36 99th 0.14 0.19 0.21 0.34

100th 0.18 0.18 0.25 0.39 101st 0.15 0.17 0.24 0.39 102nd 0.15 0.26 0.14 0.30 103rd 0.17 0.19 0.23 0.34 104th 0.16 0.20 0.21 0.29 105th 0.16 0.19 0.24 0.36 106th 0.16 0.17 0.25 0.37 107th 0.17 0.17 0.29 0.47 108th 0.18 0.18 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

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

Total number of bills sponsored by j and cosponsored by i More bills in common = stronger relationship

Weighted cosponsorship distance

ij ijwac=∑l ll

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 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.

()min,kjki ijddd+

Results for the HouseCongress Best Connected Legislator Strongest Sponsor / Cosponsor Relation Relationship

House 93rd 0.44 Koch, Edward [D-NY-18] 69 Staggers, Harley [D-WV-2] / Devine, Samuel [R-OH-12] Commerce Chair, Ranking Member 94th 0.57 Pepper, Claude [D-FL-14] 72 Price, Melvin [D-IL-21] / Wilson, Robert [R-CA-41] Armed Services Chair, Ranking Member 95th 0.60 Pepper, Claude [D-FL-14] 51 Price, Melvin [D-IL-21] / Wilson, Robert [R-CA-41] Armed Services Chair, Ranking Member 96th 0.31 Pepper, Claude [D-FL-14] 58 Price, Melvin [D-IL-21] / Wilson, Robert [R-CA-41] Armed Services Chair, Ranking Member 97th 0.27 Montgomery, G. [D-MS-3] 29 Price, Melvin [D-IL-21] / Dickinson, William [R-AL-2] Armed Services Chair, Ranking Member 98th 0.27 Roe, Robert A. [D-NJ-8] 30 Price, Melvin [D-IL-21] / Dickinson, William [R-AL-2] Armed Services Chair, Ranking Member 99th 0.26 Breaux, John [D-LA-7] 16 Montgomery, G. [D-MS-3] / Hammerschmidt, J. [R-AR-3] Ve terans Affair s Chair, Ranking Member

100th 0.25 Waxman, Henry A. [D-CA-29] 57 Montgomery, G. [D-MS-3] / Solomon, Gerald [R-NY-24] Ve terans Affair s Chair, Ranking Member 101st 0.28 Stark, Fortney Pete [D-CA-9] 23 Schulze, Richard T. [R-PA-5] / Yatron, Gus [D-PA-6] Contiguous Districts 102nd 0.27 Fawell, Harris W. [R-IL-13] 14 Hughes, William [D-NJ-2] / Moorhead, Carlos [R-CA-22] Courts and Intellectual Property Chair, Ranking Member 103rd 0.22 Waxman, Henry A. [D-CA-29] 8 Hughes, William [D-NJ-2] / Moorhead, Carlos [R-CA-27] Courts and Intellectual Property Chair, Ranking Member 104th 0.24 Traficant, James [D-OH-17] 7 Moorhead, Carlos [R-CA-27] / Schroeder, Pat [D-CO-1] Courts and Intellectual Property Chair, Ranking Member 105th 0.22 Gilman, Benjamin [R-NY- 20] 7 Ensign, John E. [R-NV-1] / Gibbons, Jim [R-NV-2] Contiguous Districts 106th 0.28 McCollum, Bill [R-FL-8] 10 Shuster, Bud [R-PA-9] / Oberstar, James L. [D-MN-8] Transportation Chair, Ranking Member 107th 0.24 Young, Don [R -AK] 11 DeMint, Jim [R-SC-4] / Myrick, Sue [R-NC-9] (Nearly) Contiguous Districts, Repub. Study Committee 108th 0.28 Saxton, Jim [R-NJ-3] 14 Ney, Robert W. [R-OH-18] / Larson, John B. [D-CT-1] House Administration Chair, Ranking

Results for the SenateCongress Best Connected Legislator Strongest Sponsor / Cosponsor Relation Relationship

Senate 93rd 0.94 Jackson, Henry [D-WA] 65 Magnuson, Warren [D-WA] / Cotton, Norris [R-NH] Commerce Chair, Ranking Member 94th 1.12 Moss, Frank [D-UT] 139 Jackson, Henry [D-WA] / Fannin, Paul [R-AZ] Interior and Insular Affairs Chair, Ranking Member 95th 0.90 Dole, Robert J. [R-KS] 33 Inouye, Daniel [D-HI] / Matsunaga, Spark [D-HI] Same State 96th 0.84 Dole, Robert J. [R-KS] 24 Byrd, Robert [D-WV] / Baker, Howard [R-TN] Majority, Minority Leader 97th 0.91 Heinz, Henry [R-PA] 34 Inouye, Daniel [D-HI] / Matsunaga, Spark [D-HI] Same State 98th 1.28 Hatch, Orrin G. [R-UT] 63 Baker, Howard [R-TN] / Byrd, Robert [D-WV] Majority, Minority Leader 99th 1.37 Thurmond, Strom [R-SC] 109 Cranston, Alan [D-CA] / Wilson, Pete [R-CA] Same State

100th 1.46 Cranston, Alan [D-CA] 70 Byrd, Robert [D-WV] / Dole, Robert J. [R-KS] Majority, Minority Leader 101st 1.39 Kennedy, Edward M. [D-MA] 77 Mitchell, George J. [D-ME] / Dole, Robert J. [R-KS] Majority, Minority Leader 102nd 1.23 Mitchell, George J. [D-ME] 179 Mitchell, George J. [D-ME] / Sasser, Jim [D-TN] Federal Housing Reform 103rd 1.20 Mitchell, George J. [D-ME] 59 Mitchell, George J. [D-ME] / Dole, Robert J. [R-KS] Majority, Minority Leader 104th 1.58 Dole, Robert J. [R-KS] 38 Dole, Robert J. [R-KS] / Daschle, Thomas A. [D-SD] Majority, Minority Leader 105th 1.36 McCain, John [R-AZ] 40 Lott, Trent [R-MS] / Daschle, Thomas A. [D-SD] Majority, Minority Leader 106th 1.36 Hatch, Orrin G. [R-UT] 104 Hutchison, Kay Bailey [R-TX] / Brownback, Sam [R-KS] Marriage Penalty Relief and Bankruptcy Reform 107th 1.61 Feingold, Russell D. [D-WI] 53 McCain, John [R-AZ] / Gramm, Phil [R-TX] Personal 108th 1.43 McCain, John [R-AZ] 50 Frist, Bill [R-TN] / Daschle, Thomas A. [D-SD] Majority, Minority Leader

Quality of Strongest Weighted Relationships Institutional Ties

House committee chairs and ranking members Senate majority and minority leaders

Regional Ties From the same state In the House they are often from contiguous districts

Issue Ties 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

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Modularity

Polarization in the 108th Senate

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108th House by Party



108th House by Ideology



108th House by State



108th House by Committee



Polarization Over Time in the House



Polarization Over Time in the Senate



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

judgesGeorge 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

an important ruling salient to the citing case a reversed opinion

Regardless of content, each citation is a latent judgment about which cases are most important 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

during this period there was no “firm doctrine of stare decisis”(Kempin 1959, 50)

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 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?

Percentage of Cases with At Least One Outward Citation by Year

1750 1800 1850 1900 1950 2000

0

20

40

60

80

100

Year

Cases With At LeastOne Outward Citation (%)

Warren Court

stare decisisin full effect

Stare Decisis and the Warren Court Warren Court (1953-1969) departs from stare decisis

Sharp decrease in outward citiations Sharp decrease in cases that do not cite any precedents

Consistent with argument Warren Court was “activist” 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 SelectedLandmark Abortion Decisions Network

HUBAUHTORITY

Importance Ranks of SelectedLandmark Abortion Decisions

5 Case Network 72 Case Network Complete Network

Decision Inward

Importance

% Rank

Outward

Importance

% Rank

Inward

Citations

Outward Citations

Inward

Importance

% Rank

Outward

Importance

% Rank

Inward Citations

Outward Citations

Inward

Importance

% Rank

Outward

Importance

% Rank

Inward Citations

Outward Citations

Roe v. Wade, 410 U.S. 113 (1973)

1.00

0.20

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

Thornburgh v. American College, 476 U.S. 747 (1986)

0.60

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

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 2005Case Inward Importance Score

(Percentile Rank) Cantwell v. Connecticut (1940) 0.1983 (1.000000) Schneider v. State (Town of Irvington) (1930) 0.1648 (.9999654) New York Times v. Sullivan (1964) 0.1567 (.9999309) Thornhill v. Alabama (1940) 0.1475 (.9998963) NAACP v. Button (1963) 0.1473 (.9998618) NAACP v. Alabama 0.1415 (.9998273) Lovell v. City of Griffin (1938) 0.1348 (.9997928) Chaplinsky v. New Hampshire (1942) 0.1158 (.9997582) McCulloch v. Maryland (1819) Shelton v. Tucker (1960)

0.1130 (.9997237) 0.1064 (.9996891)

Stromberg v. California (1931) 0.1047 (.9996546) Roth v. U.S. (1957) 0.1046 (.9996200) Near v. Minnesota (1931) 0.1038 (.9995855) Speiser v. Randall (1958) 0.1030 (.9995509) Thomas v. Collins (1945) 0.1022 (.9995164) Hague v. Committee for Industrial Org. (1951) 0.1015 (.9994819) Buckley v. Valeo (1976) 0.1012 (.9994473) Pierce v. Society of Sisters (1925) 0.1007 (.9994128) DeJonge v. Oregon (1937) 0.0936 (.9993783) Whitney v. California (1927) 0.0892 (.9993437)

Top 20 Outward Important Cases in 2005Case Outward Importance

Score (Percentile Rank) First National Bank v. Bellotti (1978) 0.1291 (1.000000) Griswold v. Connecticut (1965) Buckley v. Valeo (1976)

0.1159 (.9999654) 0.1157 (.9999309)

Dennis v. U.S. (1951) Young v. American Mini Theatres Inc. (1976)

0.1079 (.9998963) 0.1073 (.9998618)

Grayned v. City of Rockford (1972) 0.1007 (.9998273) Kovacs v. Cooper (1949) 0.0899 (.9997928) 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)

0.0936 (.9997582) 0.0932 (.9997237) 0.0920 (.9996891)

VA State Board of Pharmacy v. VA Citizens Consumer Council (1976) 0.0917 (.9996546) Roe v. Wade (1973) 0.0893 (.9996200) American Communications Assn. v. Douds (1950) 0.0888 (.9995855) Richmond Newspapers Inc. v. VA (1980) 0.0861 (.9995509) Consol. Edison Co. of NY v. Public Service Commission of NY (1980) 0.0855 (.9995164) NAACP v. Claiborne Hardware Co. (1982) 0.0848 (.9994819) New York v. Ferber (1982) 0.0837 (.9994473) Metromedia v. City of San Diego (1981) 0.0814 (.9994128) New York Times. V. Sullivan (1964) 0.0796 (.9993783) R.A.V. v. City of St. Paul (1992) 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 Dependent Variable: Number of Times a U.S. Supreme Court Case is Cited by

the U.S. Supreme Court in the Following Year Importance Measure:

Inward

Importance

Outward Importance

Inward

Cites

Outward

Cites

Inward Eigenvector Centrality

Outward Eigenvector Centrality

New York Times

Amici

Briefs

CQ

List

Oxford

List

Importance Measure

3.32 (0.03)

2.76 (0.04)

0.065 (0.001)

0.041 (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)

Lagged Dep. Variable

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)

Ln(Age)

-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 (0.001)

-0.009 (0.001)

-0.022 (0.001)

-0.014 (0.001)

-0.023 (0.001)

-0.007 (0.001)

-0.039 (0.002)

-0.040 (0.002)

-0.016 (0.001)

-0.018 (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)

Log Pseudo-Likelihood

-571443 -584038 -579838 -599022 -603595 -600182 -128951 -129611 -600991 -606027

Null Likelihood -710668 -710668 -710668 -710668 -710668 -710668 -142503 -142503 -707601 -708910

N 2485411 2485411 2485411 2485411 2485411 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

Dependent Variable: Number of Times a U.S. Supreme Court Case is Cited by the U.S. Court of Appeals in the Following Year

Importance Measure:

Inward

Importance

Outward Importance

Inward

Cites

Outward

Cites



New York Times

Amici

Briefs

CQ

List

Oxford

List

Importance Measure

2.14 (0.03)

1.85 (0.03)

0.064 (0.001)

0.046 (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)

Ln(Age)

-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 (0.001)

-0.011 (0.001)

-0.02 (0.001)

-0.014 (0.001)

-0.019 (0.001)

-0.007 (0.001)

-0.023 (0.001)

-0.023 (0.001)

-0.016 (0.001)

-0.017 (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

Null Likelihood -1829049 -1829049 -1829049 -1829049 -1829049 -1829049 -481819 -481819 -1809860 -1817550

N 2485411 2485411 2485411 2485411 2485411 2485411 198884 198884 2482076 2483569

Relationship Between Importance Measures and Future Citations of U.S. Supreme Court Precedent by State Courts, 1792-2005

Dependent Variable: Number of Times a U.S. Supreme Court Case is Cited by State Courts in the Following Year

Importance Measure:

Inward

Importance

Outward Importance

Inward

Cites

Outward

Cites



New York Times

Amici

Briefs

CQ

List

Oxford

List

Importance Measure

2.54 (0.03)

1.98 (0.05)

0.065 (0.001)

0.039 (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)

Ln(Age)

-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 (0.001)

-0.011 (0.001)

-0.020 (0.000)

-0.015 (0.001)

-0.022 (0.001)

-0.011 (0.001)

-0.019 (0.001)

-0.018 (0.001)

-0.017 (0.000)

-0.018 (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

Null Likelihood -1931174 -1931174 -1931174 -1931174 -1931174 -1931174 -430155 -430155 -1918232 -1923021

N 2485411 2485411 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. 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 Alternative Importance Measure:

Inward

Cites

Outward

Cites



New York Times

Amici

Briefs

CQ

List

Oxford

List

Inward Importance 73.8 (0.8)

103.6 (0.5)

101.0 (1.4)

106.2 (1.3)

56.9 (1.2)

59.6 (1.2)

97.6 (1.2)

99.9 (1.1)

Outward Importance 35.7 (0.9)

32.6 (1.6)

46.1 (1.6)

38.0 (1.9)

60.0 (1.8)

61.2 (1.9)

39.2 (1.6)

42.0 (1.4)

Alternative Importance Measure 33.1 (0.8)

10.4 (0.5)

4.1 (0.9)

8.4 (1.1)

9.5 (0.9)

6.7 (0.9)

12.0 (0.5)

11.1 (0.5)

Log Likelihood Ratio 23707 33953 37219 33887 5624 6191 39694 44041 N 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 Alternative Importance Measure:

Inward

Cites

Outward

Cites



New York Times

Amici

Briefs

CQ

List

Oxford

List


58.2 (1.1)

84.0 (1.3)

66.1 (1.1)

34.9 (1.6)

34.6 (1.5)

55.1 (1.0)

56.9 (1.0)


10.9 (1.3)

25.1 (1.1)

-5.5 (1.4)

32.0 (1.9)

31.8 (1.9)

25.3 (1.1)

27.0 (1.1)


21.7 (0.9)

-23.3 (1.2)

62.6 (1.4)

-1.1 (0.9)

-0.7 (0.9)

9.3 (0.5)

7.0 (0.6)


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 Alternative Importance Measure:

Inward

Cites

Outward

Cites



New York Times

Amici

Briefs

CQ

List

Oxford

List


79.9 (1.2)

83.7 (1.5)

80.9 (1.2)

56.0 (1.9)

56.0 (1.9)

76.8 (1.1)

77.3 (1.1)


18.0 (1.5)

25.6 (1.4)

24.2 (1.7)

66.1 (2.9)

66.6 (2.9)

23.1 (1.4)

24.9 (1.3)


9.3 (0.6)

-2.8 (1.3)

2.3 (1.3)

-1.0 (1.0)

-2.6 (1.3)

9.7 (0.6)

8.7 (0.7)


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 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



Changing Importance of Commerceand Civil Rights Issues



Fifth Amendment Cases



Come Get the Citation Data! http://jhfowler.ucsd.edu/judicial.htm

http://jhfowler.ucsd.edu/judicial.htm

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