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Wordfish Scaling/证据
方法证据记录

Wordfish Scaling

Wordfish scaling is an unsupervised text-as-data method that estimates a single latent position for each political document — a party manifesto, a legislative speech, a press release — directly from its word frequencies, without any reference texts or hand coding. Introduced by Slapin and Proksch in 2008, it models word counts as draws from a Poisson distribution whose rate depends on a document position and word-specific parameters, recovering, for example, a left–right ordering of parties purely from how often each word appears in each text.

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源记录

引文逐字复制自方法源记录。这些引文不代表任何层级的验证。

Wordfish Scaling of Political Texts (Unsupervised Position Estimation)
分类方法记录 · latent-structure / political-science
  • Slapin, J. B., & Proksch, S.-O. (2008). A Scaling Model for Estimating Time-Series Party Positions from Texts. American Journal of Political Science, 52(3), 705–722. · DOI 10.1111/j.1540-5907.2008.00338.x
  • Lowe, W., & Benoit, K. (2013). Validating Estimates of Latent Traits from Textual Data Using Human Judgment as a Benchmark. Political Analysis, 21(3), 298–313. · DOI 10.1093/pan/mpt002
  • Grimmer, J., & Stewart, B. M. (2013). Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts. Political Analysis, 21(3), 267–297. · DOI 10.1093/pan/mps028
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Same method familyIdeal Point Estimationmachine-suggested · Relational suggestion, not evidence.Used in the same domainManifesto Codingmachine-suggested · Relational suggestion, not evidence.Same method familyWordfishmachine-suggested · Relational suggestion, not evidence.Same method familyWordscoresmachine-suggested · Relational suggestion, not evidence.

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Bibliographic sources are present. Claim-level evidence review has not been performed.

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