A general class of social distance measures

Graham Brown, A. Langer

Research output: Contribution to journalArticle

1 Citation (Scopus)
11 Downloads (Pure)

Abstract

© The Author 2016. Measures of diversity and disparity within a population are used for investigating a range of developmental outcomes, but often by employing "off-the-shelf" indicators that may not be theoretically appropriate for the hypotheses under investigation. In this article, we proposed a general class of social distance measures that both enables us to see the conceptual relationship between different existing measures of heterogeneity more clearly and is sufficiently flexible to allow for the development of tailored hypothesis-specific measures. We show how a range of existing aggregate measures of diversity and disparity fit within the general class and demonstrate illustratively how the measure can be used to develop more precise hypothesis-specific measures.
Original languageEnglish
Pages (from-to)211-225
JournalPolitical Analysis
Volume24
Issue number2
DOIs
Publication statusPublished - 2016

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Brown, Graham ; Langer, A. / A general class of social distance measures. In: Political Analysis. 2016 ; Vol. 24, No. 2. pp. 211-225.
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A general class of social distance measures. / Brown, Graham; Langer, A.

In: Political Analysis, Vol. 24, No. 2, 2016, p. 211-225.

Research output: Contribution to journalArticle

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AB - © The Author 2016. Measures of diversity and disparity within a population are used for investigating a range of developmental outcomes, but often by employing "off-the-shelf" indicators that may not be theoretically appropriate for the hypotheses under investigation. In this article, we proposed a general class of social distance measures that both enables us to see the conceptual relationship between different existing measures of heterogeneity more clearly and is sufficiently flexible to allow for the development of tailored hypothesis-specific measures. We show how a range of existing aggregate measures of diversity and disparity fit within the general class and demonstrate illustratively how the measure can be used to develop more precise hypothesis-specific measures.

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