RELTRAD2: Refining the State of the Art of Religious Classification by Reconsidering the Categorization of Nondenominational Respondents.

RELTRAD is a major religious taxonomy used by a large number of researchers. Although criticisms have been raised about its utility, improving the algorithm to capture contemporary religious dynamics is important given its widespread use. The present RELTRAD taxonomy classifies more religiously acti...

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Publicado en:Journal for the Scientific Study of Religion (John Wiley & Sons, Inc.) Vol. 63; no. 3; pp. 638 - 656
Autores principales: Gaghan, Josh, Eagle, David
Formato: Artículo
Publicado: John Wiley & Sons, Inc. Sep2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2024
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        au:
          Gaghan, Josh
          Eagle, David
        affil:
          Duke Global Health Institute, Duke University
          Department of Sociology, Duke Global Health Institute, Duke University
      su:
        Christians
        Protestants
        Religious groups
        Independent churches
        Race identity
        Taxonomy
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        subj:
          Christians
          Protestants
          Religious groups
          Independent churches
          Race identity
          Taxonomy
      keyword:
        religion
        religious classification
        RELTRAD
      ab: RELTRAD is a major religious taxonomy used by a large number of researchers. Although criticisms have been raised about its utility, improving the algorithm to capture contemporary religious dynamics is important given its widespread use. The present RELTRAD taxonomy classifies more religiously active nondenominational respondents as Conservative Protestants and codes the remainder as missing data. A growing number of Americans indicate they are either nondenominational or only Christian or Protestant, which means using RELTRAD in its existing form codes a nonrandom and increasingly large number of respondents with a missing value for religious affiliation (growing from 2 percent to 5 percent of the US General Social Survey (GSS) sample between 2000 and 2018). Using a machine learning algorithm to predict the likely religious tradition of nondenominational respondents, we demonstrate the shortcomings of this approach and introduce a new coding scheme, RELTRAD2, which classifies nondenominational respondents who report a Black racial identity as Black Protestant, non‐Black respondents who never attend religious services as Mainline Protestant, and the remainder as Conservative Protestant. Code to derive RELTRAD2 from the GSS is provided.
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