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多样性及其分解为种类、平衡和差异。

Diversity and its decomposition into variety, balance and disparity.

作者信息

van Dam Alje

机构信息

Copernicus Institute of Sustainable Development and the Centre for Complex Systems Studies (CCSS), Utrecht University, Utrecht, The Netherlands.

出版信息

R Soc Open Sci. 2019 Jul 17;6(7):190452. doi: 10.1098/rsos.190452. eCollection 2019 Jul.

Abstract

Diversity is a central concept in many fields. Despite its importance, there is no unified methodological framework to measure diversity and its three components of variety, balance and disparity. Current approaches take into account disparity of the types by considering their pairwise similarities. Pairwise similarities between types may not adequately capture total disparity, since they do not take into account in which way pairs are similar. Hence, pairwise similarities do not discriminate between similarities of types in terms of the same feature and similarities in which all pairs share different features. This paper presents an alternative approach which is based on the overlap of features over the whole set of types. This results in a measure of diversity that takes into account the aspects of variety, balance and disparity. Based on this measure, the ' decomposition' is introduced, which provides separate measures for the variety, balance and disparity, allowing them to enter analysis separately. The method is illustrated by analysing the industrial diversity from 1850 to present while taking into account the overlap in occupations they employ. Finally, the framework is extended to take into account disparity considering multiple features, providing a helpful tool in analysis of high-dimensional data.

摘要

多样性是许多领域的核心概念。尽管其很重要,但目前尚无统一的方法框架来衡量多样性及其三个组成部分:种类、平衡和差异。当前的方法通过考虑类型之间的成对相似性来考量类型的差异。类型之间的成对相似性可能无法充分捕捉总体差异,因为它们没有考虑成对相似的方式。因此,成对相似性无法区分同一特征方面的类型相似性和所有成对都具有不同特征的相似性。本文提出了一种基于所有类型特征重叠的替代方法。这产生了一种考虑种类、平衡和差异方面的多样性度量。基于这种度量,引入了“分解”,它为种类、平衡和差异提供了单独的度量,使它们能够分别进入分析。通过分析1850年至今的产业多样性并考虑所雇佣职业的重叠情况来说明该方法。最后,该框架被扩展以考虑多个特征的差异,为高维数据分析提供了一个有用的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/379d/6689592/a6f0ad574447/rsos190452-g1.jpg

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