Updated February 8, 2018
Downloading data from this page implies that agreement with the following restrictions:
- These data are not to be used for commercial or for-profit use.
- These data may not be sold or otherwise restricted to others.
- These data may be used only for research, academic or scholarly pursuits to advance knowledge in related fields.
- George Mason University and Jennifer Victor are not responsible for violations of these intended usages of these data.
- Please cite your usage of these data using the following citation:
Victor, Jennifer Nicoll. 2018. “NAME OF DATASET.” Data available for scholarly use from https://jvictor.gmu.edu/index.php/data-download/ DATE ACCESSED.”
If you find errors, please communicate them to jvictor3@gmu.edu. I will post notes and updated data as time permits.
U.S. Congress Caucus Data
For complete caucus membership data from the 103rd to 113th congresses, please visit: http://bridgeinfogap.org/database/
Caucus Membership
The files called “membership_xxx.csv” are incidence matrices where the first column indicates the MC identifier and the first row indicates the caucus identifier. Values are dichotomous, where 1= caucus membership.
membership_109.csv
membership_110.csv
membership_111.csv
Caucus Leadership
The files called “leadership_xxx.csv” are incidence matrices where the first column indicates the MC identifier and the first row indicates the caucus identifier. Values are dichotomous, where 1 = caucus leader.
leadership_109.csv
leadership_110.csv
leadership_111.csv
Caucuses
The files called “Caucuses_xxx.csv” contain two columns. The first column indicates the caucus identifier. The second column indicates the caucus name, a string. The first row has column labels.
caucuses_109.csv
caucuses_110.csv
caucuses_111.csv
Cosponsorship Data
The following files were created with assistance from Justin Kirkland. The bill data were scraped from Thomas. Matrices are incidence files with MCs as rows (with IDs in the first column) and bills in columns. 1 = sponsorship, 2 = cosponsorship. Some MCs are removed from these files so that IDs and MCs match caucus data. See notes. Files are in comma separated values (.csv) format. As of now, only House data are included.
Cosponsorship_103
Cosponsorship_104
Cosponsorship_105
Cosponsorship_106
Cosponsorship_107
Cosponsorship_108
Cosponsorship_109
Cosponsorship_110
Cosponsorship_111
Co-voting Data
These data were compiled with assistance from Steven Haptonstahl and Justin H. Gross. Data below are Excel files (.xlsx) that include square adjacency matrices of co-voting for the 103rd-111th congresses, with legislator IDs. Legislators are coded as 1 if they voted “Yea” or were recorded as an “Announced Yea” vote (originally, 1 and 3, respectively in raw roll call data). Legislators are coded as -1 if they voted “Nay” or “Announced Nay” (originally 6 and 4 in raw data, respectively). Those voting “Present” (7) or “Not Voting” (9) are coded as 0.
Procedure:
- Calculate the sum (S) of all the dyadwise agreements (1s) and disagreements (-1).
- Calculate the sum of the absolute values of all votes (V), which returns the number of roll calls in which both members of the dyad participated.
- Calculate the number of times the dyad cast the same vote (A): (S+V)/2
- Calculate the rate of agreement for each dyad, given that both voted: A / V
The matrices report the rate of voting agreement for each dyad in each congress across all roll call votes for the House.
Covoting_103H.xlsx
Covoting_104H.xlsx
Covoting_105H.xlsx
Covoting_106H.xlsx
Covoting_107H.xlsx
Covoting_108H.xlsx
Covoting_109H.xlsx
Covoting_110H.xlsx
Covoting_111H.xlsx