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The Dimensionality of Congressional Voting Reconsidered

Dados Bibliográficos

ID6179357
AutoresJason M Roberts (0000-0001-8113-1827, University of North Carolina at Chapel Hill, autor correspondente), Stephanie S Smith (0000-0001-9943-6717, Washington University in St. Louis), Steven S Smith, Stephen R Haptonstahl (National Public Radio)
Ano2016
Volume44
Fascículo5
Páginas794-815
Data de publicação2016-09-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoAmerican Politics Research (JOURNAL)
Identificadores do periódicoISSN: 1532-673X • E-ISSN: 1552-3373
EditoraSAGE Publications Inc (PUBLISHER)
DOI10.1177/1532673x15608940
OpenAlexW2255276142
IdiomaEN
Citações recebidas8
Referências citadas26

This article reports findings for a decomposition of the roll-call voting record of the U.S. Congress to determine the effect of the level of aggregation on the observed dimensionality of the policy space. In doing so, we identify some but certainly not all of the ways in which the aggregation of the voting record affects the observed dimensionality of the policy space. For the 1955 to 2008 period (84th-110th Congresses), we apply optimal classification (OC) to votes aggregated to the level of the individual bill and policy area to measure dimensionality. We examine the marginal proportional reduction in error (MPRE) across dimensions. Our results demonstrate that complexity in voting patterns of individual bill episodes is the norm, that aggregating to higher levels reduces the observed dimensionality, and that the liberal–conservative dimension appears more dominant in more highly aggregated analyses. These results call into question many of the conclusions from the theoretical and empirical literature on the U.S. Congress that uses a unidimensional model

Combinatorics · Curse of dimensionality · Dimensionality reduction · Econometrics · Economics · Political science · Politics · Statistics · Voting · Computer Science · Electoral Systems and Political Participation · Fiscal Policies and Political Economy · Law · Mathematics · Media Influence and Politics · Artificial Intelligence

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Obras citantes distintas8
Citações por ano1
Intervalo de citações2018 - 2026 (9)
Velocidade de citaçãocurrent
Altamente citadoNão
Tipos de citaçãoNeutras: 8
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