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Below results based on the criteria 'cosponsorship'
Total number of records returned: 3
Cosponsorship Coalitions in the U.S. House of Representatives
Grant, J. Tobin
Pellegrini, Pasquale (Pat) A.
urrent theories and methods for studying of cosponsorship assume that the decision to cosponsor is identical to decision to vote. In this paper we develop a new theory of cosponsorship that identifies where along the ideological spectrum cosponsors of a bill are more likely to be. Moreover, we predict that members with organizational ties to the sponsor are more likely to cosponsor than other members. To test this theory, we employ a spatial duration model. This method has recently been used by geographers to estimate areas that are more likely to experience an "event." Using this technique permits a statistical test that supports our substantive hypotheses that cosponsorship coalitions are shaped by the characteristics of the location of the bill, the shared ties to the sponsor, and the policy area. In addition, more active sponsors are associated with wider and less clustered coalitions. These findings demonstrate that theories of the voting decision are not applicable to cosponsorship.
Estimating Proposal and Status Quo Locations Using Voting and Cosponsorship Data
Ideal Point Estimation
Theories of Lawmaking
Theories of lawmaking generate predictions for the policy outcome as a function of the status quo. These theories are difficult to test because existing ideal point estimation techniques do not recover the locations of proposals or status quos. Instead, such techniques only recover cutpoints. This limitation has meant that existing tests of theories of lawmaking have been indirect in nature. I propose a method of directly measuring ideal points, proposal locations, and status quo locations on the same multidimensional scale, by employing a combination of voting data, bill and amendment cosponsorship data, and the congressional record. My approach works as follows. First, we can identify the locations of legislative proposals (bills and amendments) on the same scale as voter ideal points by jointly scaling voting and cosponsorship data. Next, we can identify the location of the final form of the bill using the location of last successful amendment (which we already know). If the bill was not amended, then the final form is simply the original bill location. Finally, we can identify the status quo point by employing the cutpoint we get form scaling the final passage vote. To implement this procedure, I automatically coded data on the congressional record available from www.thomas.gov. I apply this approach to recent sessions of the U.S. Senate, and use it to test the implications of competing theories of lawmaking.
Cosponsorship in the U.S. Senate: A Multilevel Approach to Detecting Subtle Social Predictors of Legilslative Support
social network analysis
Why do members of Congress choose to cosponsor legislation proposed by their colleagues and what can we learn from their patterns of cosponsorship? To answer these questions properly requires models that respect the relational nature of the relevant data and the resulting interdependence among observations. We show how the inclusion of carefully selected random effects can capture network-type dependence, allowing us to more confidently investigate senators' propensity to support colleagues' proposals. To illustrate, we examine whether certain social factors such as demographic similarities, opportunities for interaction, and institutional roles are associated with varying odds of cosponsorship during the 2003-04 (108th) Senate.