Measuring electoral democracy with observables.
Most cross‐national indices of democracy rely centrally on coder judgments, which are susceptible to bias and error, and require expensive and time‐consuming coding by experts. We present an approach to measurement based on observables that aim to preserve the nuanced quality of subjectively coded d...
| Publicado en: | American Journal of Political Science (John Wiley & Sons, Inc.) Vol. 70; no. 2; pp. 606 - 623 |
|---|---|
| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
John Wiley & Sons, Inc.
Apr2026
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=193087455&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 193087455 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00925853 LVDV jtl: American Journal of Political Science (John Wiley & Sons, Inc.) issn: 00925853 maglogo: N pubinfo: dt: Apr2026 vid: 70 iid: 2 pid: 52269 pub: John Wiley & Sons, Inc. artinfo: ui: 193087455 10.1111/ajps.12968 ppf: 606 ppct: 17 formats: tig: atl: Measuring electoral democracy with observables. aug: au: Weitzel, Daniel Gerring, John Pemstein, Daniel Skaaning, Svend‐Erik affil: Department of Political Science, Colorado State University, Fort Collins Colorado,, USA Department of Government, University of Texas at Austin, Austin Texas,, USA Department of Political Science and Public Policy, North Dakota State University, Fargo North Dakota,, USA Department of Political Science, Aarhus University, Aarhus, Denmark su: Measurement Random forest algorithms Empirical research Democracy Index numbers (Economics) sug: subj: Measurement Random forest algorithms Empirical research Democracy Index numbers (Economics) ab: Most cross‐national indices of democracy rely centrally on coder judgments, which are susceptible to bias and error, and require expensive and time‐consuming coding by experts. We present an approach to measurement based on observables that aim to preserve the nuanced quality of subjectively coded democracy indices. Our observable‐to‐subjective score mapping is free of idiosyncratic coder errors arising from misinformation, slack, or biases. It is less susceptible to systematic bias that may arise from coders' inferences about a country's regime, for example, from the ideology of the ruler. The data collection procedure and mode of analysis are fully transparent and replicable, and the procedure is based on random forests and is cheap to produce, easy to update, and offers coverage for all polities with sovereign or semisovereign status, surpassing the sample of any existing index. We show that this expansive coverage makes a big difference to our understanding of some causal questions. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2026 holdings: @attributes: islocal: N |
|---|