The DOI matches its Crossref record.
Patterns of Congressional Voting
Abstract
Congressional roll call voting has been highly structured for most of U.S. history. The structure is revealed by a dynamic, spatial analysis of the entire roll call voting record from 1789 to 1985. The space is characterized by a predominant major dimension with, at times, a significant, but less important second dimension. In the modern era, spatial positions are very stable. This stability is such that, under certain conditions, short run forecasting of roll call votes is possible. Since the end of World War II, changes in congressional voting patterns have occurred almost entirely through the process of replacement of retiring or defeated legislators with new members. Politically, selection is far more important than adaptation.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Respect for Human Rights has Improved Over Time: Modeling the Changing Standard of Accountability
FARISS, C. J. (2014) · American Political Science Review · doi:10.1017/s0003055414000070 · Cited by 706
Mapping the Ideological Marketplace
Bonica, A. (2014) · American Journal of Political Science · doi:10.1111/ajps.12062 · Cited by 680
Biased assimilation, homophily, and the dynamics of polarization
Dandekar, P., Goel, A., & Lee, D. T. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217220110 · Cited by 435
Political Ideologies and Political Parties in America
Noel, H. (2014) · doi:10.1017/cbo9781139814775 · Cited by 365
The Effect of the Expansion of the Voting Franchise on the Size of Government
Husted, T. A., & Kenny, L. W. (1997) · Journal of Political Economy · doi:10.1086/262065 · Cited by 330
Jackman, S. (2001) · Political Analysis · doi:10.1093/polana/9.3.227 · Cited by 281
Biased Assimilation, Homophily, and the Dynamics of Polarization
Dandekar, P., Goel, A., & Lee, D. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-35311-6_47 · Cited by 201
Bolton, P., Li, T., Ravina, E., & Rosenthal, H. (2020) · Journal of Financial Economics · doi:10.1016/j.jfineco.2020.03.004 · Cited by 183
Self-citationEstimating Legislators' Preferred Points
Londregan, J. (1999) · Political Analysis · doi:10.1093/oxfordjournals.pan.a029804 · Cited by 159
Measuring the complexity of the law: the United States Code
Katz, D. M., & Bommarito, M. J. (2014) · Artificial Intelligence and Law · doi:10.1007/s10506-014-9160-8 · Cited by 117
SHOR, B., BERRY, C., & MCCARTY, N. (2010) · Legislative Studies Quarterly · doi:10.3162/036298010792069198 · Cited by 100
Leech, B. L. (2010) · The Oxford Handbook of American Political Parties and Interest Groups · doi:10.1093/oxfordhb/9780199542628.003.0028 · Cited by 91
Congleton, R. D. (2001) · Public Choice · doi:10.1023/a:1010337412291 · Cited by 83
Knowing Left from Right: Ideological Identification in Brazil, 2002-2006
Ames, B., & Smith, A. E. (2010) · Journal of Politics in Latin America · doi:10.1177/1866802x1000200301 · Cited by 68
Theory In, Theory Out: The Uses of Social Theory in Machine Learning for Social Science
Radford, J., & Joseph, K. (2020) · Frontiers in Big Data · doi:10.3389/fdata.2020.00018 · Cited by 58
Metadata
- Authors
- Poole, K. T., & Rosenthal, H.
- Venue
- American Journal of Political Science
- Publisher
- JSTOR
- Published
- 1991-02
- Volume
- 35
- Issue
- 1
- Pages
- 228
- ISSN
- 0092-5853 (ISSN-L)
- OpenAlex
- W1482828348
- Cited by
- 777
- References
- 0
- FWCI
- 97.97
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.