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The application of a topological clustering technique to capture forms and dynamics of deprivation in contemporary Switzerland

Author

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  • Mario Lucchini

    (University of Milano Bicocca)

  • Christine Butti

    (University of Applied Science and Arts of Southern Switzerland)

  • Sara Della Bella

    (University of Applied Science and Arts of Southern Switzerland)

  • Angela Lisi

    (University of Applied Science and Arts of Southern Switzerland)

Abstract

This paper proposes the application of an innovative technique of clustering and projection—the Self-Organizing Map—in order to identify multidimensional patterns of deprivation in contemporary Switzerland. Starting from a rich set of non-monetary indicators from the Swiss Household Panel, a topological map has been extrapolated. This map is composed of 32 micro-clusters that are subsequently grouped into four macro-clusters, each of which expresses a specific profile. The analysis carried out indicates that about one out of two individuals living in Switzerland enjoy a state of multidimensional well-being, one in three shows signs of slight vulnerability, one in five is in a condition of consistent vulnerability and one in twenty is deprived. After having outlined the space of multidimensional patterns, the movements of these individuals have been reconstructed from 1999 to 2012 and the role of “true path dependence’ have been measured.

Suggested Citation

  • Mario Lucchini & Christine Butti & Sara Della Bella & Angela Lisi, 2018. "The application of a topological clustering technique to capture forms and dynamics of deprivation in contemporary Switzerland," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 227-248, January.
  • Handle: RePEc:spr:qualqt:v:52:y:2018:i:1:d:10.1007_s11135-016-0464-5
    DOI: 10.1007/s11135-016-0464-5
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    Cited by:

    1. Heyuan You & Deshao Zhou & Shenyan Wu & Xiaowei Hu & Chenmeng Bie, 2020. "Social Deprivation and Rural Public Health in China: Exploring the Relationship Using Spatial Regression," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(3), pages 843-864, February.

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