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Manifesto Coding×Ideal Point Estimation×
DziedzinaPolitical SciencePolitical Science
RodzinaProcess / pipelineLatent structure
Rok powstania20012004
TwórcaManifesto Research Group / Comparative Manifesto Project (CMP/MARPOR)Clinton, Jackman & Rivers (Bayesian formulation); Poole & Rosenthal (spatial tradition)
TypQuantitative content analysis of party manifestosLatent-variable spatial model of binary choice data
Źródło pierwotneBudge, I., Klingemann, H.-D., Volkens, A., Bara, J., & Tanenbaum, E. (2001). Mapping Policy Preferences: Estimates for Parties, Electors, and Governments 1945–1998. Oxford: Oxford University Press. ISBN: 9780199244003Clinton, J., Jackman, S., & Rivers, D. (2004). The Statistical Analysis of Roll Call Data. American Political Science Review, 98(2), 355–370. DOI ↗
Inne nazwyCMP coding, MARPOR coding, Manifesto content analysis, Party manifesto codingIdeal point model, Item response theory for roll calls, Spatial voting model, Bayesian ideal points
Pokrewne44
PodsumowanieManifesto coding is the quantitative content-analysis methodology of the Comparative Manifesto Project (CMP/MARPOR) for measuring parties' policy preferences from their election manifestos. Trained coders break each manifesto into quasi-sentences and assign every unit to one of a fixed set of policy categories. Counting how often each category appears yields salience measures, and combining pro- and anti- categories produces position scores such as the left–right RILE index, giving comparable estimates of party positions across more than fifty democracies since 1945.Ideal point estimation recovers the latent policy positions — ideal points — of political actors from their observed binary choices, most often legislators' yea/nay votes on roll calls. Building on the spatial theory of voting and formalized as a Bayesian item-response model by Clinton, Jackman, and Rivers in 2004, it places each legislator and each bill in a low-dimensional policy space and estimates positions so that the probability a legislator votes yea increases as the bill's 'yea' outcome moves closer to that legislator's ideal point.
ScholarGateZbiór danych
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  3. PUBLISHED
  1. v1
  2. 3 Źródła
  3. PUBLISHED

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ScholarGatePorównaj metody: Manifesto Coding · Ideal Point Estimation. Pobrano 2026-06-24 z https://scholargate.app/pl/compare