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New subject classification for bias-free calculation of university profile maps

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  • Fuchs, Joel Emanuel
  • Heinze, Thomas

    (University of Wuppertal)

Abstract

This paper presents a classification of teaching and research fields at universities that allows an unbiased calculation of disciplinary profiles using heat maps. This new classification and the disciplinary profiles derived from it are based on the Activity Index (AI), which can be converted by an appropriate transformation into an index with symmetric value range (RESP). Using public universities in Germany as an example, we show why both AI and RESP values are biased when data sets with many missing or zero values are used, how such a bias manifests itself, and how the new classification enables a bias-free calculation of disciplinary profiles.

Suggested Citation

  • Fuchs, Joel Emanuel & Heinze, Thomas, 2023. "New subject classification for bias-free calculation of university profile maps," SocArXiv uaxbf, Center for Open Science.
    • Handle: RePEc:osf:socarx:uaxbf
    DOI: 10.31219/osf.io/uaxbf
    as

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