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Data set codebook.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 27.8 KB 12/21/2021 03:08:PM
Important Congressional Votes, 1991-2010.dta application/x-stata-dta 4.4 MB 12/21/2021 03:19:PM

Project Citation: 

Tama, Jordan. Important Congressional Votes, 1991-2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-12-21.

Project Description

Summary:  View help for Summary This data set is designed to facilitate analysis of voting patterns in the U.S. Congress on important issues, with a focus on the alignments of Democrats and Republicans. Unlike most other data sets, the data set only includes votes on important legislation, facilitating the analysis of voting patterns on legislation with significant ramifications. At the same time, the data set includes both roll call votes and voice votes, enabling researchers to generate more accurate conclusions about the actual prevalence of polarization and bipartisanship in Congress. The data set also includes several measures designed to capture different dimensions of polarization and bipartisanship, enabling the examination of patterns related to inter-party, intra-party, and intra-branch agreement and disagreement. Finally, the data set includes variables representing the policy area covered by legislation, facilitating analysis of how political alignments vary across policy areas, particularly between foreign and domestic policy and among different areas of foreign policy.

Scope of Project

Subject Terms:  View help for Subject Terms Congress; United States Congress; political partisanship; Polarization; Bipartisanship; Foreign policy; US foreign policy; Legislation; Democrats; Republicans
Geographic Coverage:  View help for Geographic Coverage United States
Time Period(s):  View help for Time Period(s) 1991 – 2020
Collection Date(s):  View help for Collection Date(s) 2017 – 2021
Data Type(s):  View help for Data Type(s) roll call voting data


Data Source:  View help for Data Source Congressional Quarterly Almanac

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