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A mathematical approach to study and forecast racial groups interactions: deterministic modeling and scenario method

Dominioni, Goran orcid logoORCID: 0000-0002-3795-2617, Marasco, Addolorata orcid logoORCID: 0000-0002-8613-7467 and Romano, Alessandro orcid logoORCID: 0000-0002-2041-5487 (2017) A mathematical approach to study and forecast racial groups interactions: deterministic modeling and scenario method. Quality & Quantity, 52 . pp. 1929-1956. ISSN 0033-5177

Abstract
Globalization and migratory fluxes are increasing the ethnic and racial diversity within many countries. Therefore, describing social dynamics requires models that are apt to capture multi-groups interactions. Building on the assumption of a relationship between multi-racial dynamics and socioeconomic status (SES), we introduce an aggregate, con- textual, and continuous index of SES accounting for measures of income, employment, expected life, and group numerosity. After, taking into account that groups’ SES assumes the form of a logit model, we propose a Lotka–Volterra system to study and forecast the interaction among racial groups. Last, we apply our methodology to describe the racial dynamics in the US society. In particular, we study the kind and the intensity of Asians– Blacks–Natives–Whites interactions in the US between 2002 and 2013. Moreover, we forecast the evolution of groups’ SES and how interracial relations will unfold between 2013 and 2018 and in three alternative stylized scenarios.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:Racial interactions; Deterministic modeling; Scenario method; Logit model; Lotka–Volterra systems
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Humanities and Social Science > School of Law and Government
Publisher:Springer
Official URL:http://dx.doi.org/10.1007%2Fs11135-017-0581-9
Copyright Information:© 2017 The Authors (CC-BY-4.0) Open Access
ID Code:25473
Deposited On:11 Feb 2021 13:41 by Thomas Murtagh . Last Modified 11 Feb 2021 13:41
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