Cosponsorship Data 280,000 bills proposed in the U.S. House and Senate from 1973 to 2004 (93rd-108th...
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Transcript of Cosponsorship Data 280,000 bills proposed in the U.S. House and Senate from 1973 to 2004 (93rd-108th...
![Page 1: 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.](https://reader036.fdocuments.net/reader036/viewer/2022070306/5516d22255034698338b459a/html5/thumbnails/1.jpg)
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
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Cosponsorship in the House
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Cosponsorship in the Senate
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Mutual Cosponsorship Relations
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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
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Weighted cosponsorship distance
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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.
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Results for the House
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Results for the Senate
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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)
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108th House Top 20
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108th Senate Top 20
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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
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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
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Landmark Legislation:An Alternative to Mayhew
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Modularity(Newman and Girvan 2004)Define modularity to be
Q = (number of edges within groups) – (expected number within groups).
Actual Number of Edges between i and j is
Expected Number of Edges between i and j is
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Modularity Matrix So Q is a sum of
over pairs (i, j) that are in the same group Or we can write in matrix form as
Where B is a new characteristic matrix, the modularity marix,
(si, sj)
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Modularity Matrix
Algorithm Calculate the leading eigenvector of the
modularity matrix Divide the vertices according to the signs of the
elements
Note that there is no need to forbid the solution with all the vertices in a single group.
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Example
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Example Applications
Books on politics The vertices represent 105 recent books sold from Amazon.com
Divide the books according to their political alignment Liberal / Conservative / Centrist
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Example
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Polarization in the 108th Senate
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108th House by Party
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108th House by Ideology
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108th House by State
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108th House by Committee
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Polarization Over Time in the House
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Polarization Over Time in the Senate
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Black Legislators in the 103rd House
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Black Legislators in the 104th House
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Black Legislators in the 108th House
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Poor Districts in the 108th House