Introducing a spatially explicit Gini measure for spatial segregation

Türk, Umut; Östh, John

doi:10.1007/s10109-023-00412-1

Cited by 4 publications

(2 citation statements)

References 45 publications

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“…Additionally, testing the Spatial Gini coefficient (see e.g. Panzera & Postiglione 2020;Türk & Östh 2023), which has been used to study the modern world, would be interesting in the Pompeian context.…”

Section: Discussionmentioning

confidence: 99%

Networks of Inequality: Access to Water in Roman Pompeii

Simelius

2024

Journal of Computer Applications in Archaeology

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The inequality of ancient life is difficult to measure, yet this article outlines a methodology to do it. Measured distances produced by the ArcGIS Network Analyst and its Closest Facility tool can be utilized as data sets to calculate the Gini coefficients of access to water in Roman Pompeii 79 CE, when the city was buried in the eruption of Mount Vesuvius. In the focus is the distance from a private dwelling to public fountains and the baths, but other aspects, such as the estimated household need for water and the capacity of the Pompeian baths, are included in the Gini calculations to form a more accurate estimation of inequality. As a result, it is possible to estimate an aspect of health inequality in Pompeii, which can be compared to other sites and eras, if their access to water is measured similarly and calculated as a Gini value.

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Section: Discussionmentioning

confidence: 99%

Networks of Inequality: Access to Water in Roman Pompeii

Simelius

2024

Journal of Computer Applications in Archaeology

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“…More recently, the ratio between a group and its subgroup's Gini indexes has been proposed as a metric for detecting between-group inequality (Türk and Östh 2023;Crema et al, forthcoming), but these approaches suffer from other limitations of the Gini index as described below.…”

Section: Association Autocorrelation and Inequalitymentioning

confidence: 99%

Local Indicators of Dispersion: A Relational Approach to Measuring Inequality

Mejía Ramón,

Munson

2024

Preprint

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This paper presents a novel approach to measuring inequality, centering on the principles of relationship and subjectivity. We describe the limitations of traditional metrics like Gini indexes in capturing the complex, inherently relational nature of inequality. By considering inequality as a series of subjective judgments made by individuals within their social cohorts, this study introduces a method where observations on inequality are aggregated both locally and globally, offering a nuanced view that accounts for both in-group and out-group disparities and proposing an inferential procedure to identify significant disparities at multiple levels. The approach is demonstrated through a case study on global wealth inequality, showcasing the dynamic and multifaceted nature of economic disparities across trading blocs.

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