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The perceived seriousness of crimes: inter-individual commonalities and differences

Author

Listed:
  • Ingwer Borg

    (Westfälische Wilhems-Universität)

  • Dieter Hermann

    (Ruprecht-Karls-Universität)

  • Wolfgang Bilsky

    (Westfälische Wilhems-Universität)

Abstract

The paper focuses on ratings of the perceived seriousness of crimes and how they can be explained in a testable scaling model (SOCID) that shows commonalities and differences among individuals. The model assumes that crimes are first represented on each person’s psychological map. This map can be described as a geometric space spanned by the crimes’ perceived attributes. When assessing the seriousness of crimes, the person positions him-/herself on this map by finding a point whose distances to the crime points express how much he/she is rejects the respective crimes. Using three representative German surveys on crime prevention, the SOCID model is positively tested for various predictions: (1) All persons in our surveys share the same psychological map of crimes; (2) a 2-dimensional map accurately describes the persons’ observed badness ratings; (3) the points representing the crimes form essentially linear manifolds on the maps; (4) the older and the more conservation-oriented a person, the more similar his/her distances to the crimes; (5) gender has no systematic effect on the distribution of person-points on the crimes’ maps.

Suggested Citation

  • Ingwer Borg & Dieter Hermann & Wolfgang Bilsky, 2023. "The perceived seriousness of crimes: inter-individual commonalities and differences," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 765-784, February.
    • Handle: RePEc:spr:qualqt:v:57:y:2023:i:1:d:10.1007_s11135-022-01379-9
    DOI: 10.1007/s11135-022-01379-9
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    References listed on IDEAS

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    1. Stylianou, Stelios, 2003. "Measuring crime seriousness perceptions: What have we learned and what else do we want to know," Journal of Criminal Justice, Elsevier, vol. 31(1), pages 37-56.
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    3. de Leeuw, Jan & Mair, Patrick, 2009. "Multidimensional Scaling Using Majorization: SMACOF in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 31(i03).
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