Native Bias : Overcoming Discrimination Against Immigrants

Donghyun Danny Choi

ISBN 10: 0691222304 / ISBN 13: 9780691222301

Edité par Princeton University Press Okt 2022, 2022

A propos de cet article

Neuware - What drives anti-immigrant bias and how it can be mitigatedIn the aftermath of the refugee crisis caused by conflicts in the Middle East and an increase in migration to Europe, European nations have witnessed a surge in discrimination targeted at immigrant minorities. To quell these conflicts, some governments have resorted to the adoption of coercive assimilation policies aimed at erasing differences between natives and immigrants. Are these policies the best method for reducing hostilities Native Bias challenges the premise of such regulations by making the case for a civic integration model, based on shared social ideas defining the concept and practice of citizenship.Drawing from original surveys, survey experiments, and novel field experiments, Donghyun Danny Choi, Mathias Poertner, and Nicholas Sambanis show that although prejudice against immigrants is often driven by differences in traits such as appearance and religious practice, the suppression of such differences does not constitute the only path to integration. Instead, the authors demonstrate that similarities in ideas and value systems can serve as the foundation for a common identity, based on a shared concept of citizenship, overcoming the perceived social distance between natives and immigrants.Addressing one of the most pressing challenges of our time, Native Bias offers an original framework for understanding anti-immigrant discrimination and the processes through which it can be overcome.

N° de réf. du vendeur 9780691222301

Détails bibliographiques

• Titre: Native Bias : Overcoming Discrimination Against Immigrants
• Éditeur: Princeton University Press Okt 2022
• Date de parution: 2022
• Langue: anglais
• ISBN à 10 chiffres: 0691222304
• ISBN à 13 chiffres: 9780691222301
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 231 L x 155 H x 23 P (en millimètres) 231 millimètres de largeur par 155 millimètres de hauteur par 23 millimètres de profondeur
• Poids: 458 grammes

A propos de ce titre

Synopsis

What drives anti-immigrant bias--and how it can be mitigated

In the aftermath of the refugee crisis caused by conflicts in the Middle East and an increase in migration to Europe, European nations have witnessed a surge in discrimination targeted at immigrant minorities. To quell these conflicts, some governments have resorted to the adoption of coercive assimilation policies aimed at erasing differences between natives and immigrants. Are these policies the best method for reducing hostilities? Native Bias challenges the premise of such regulations by making the case for a civic integration model, based on shared social ideas defining the concept and practice of citizenship.

Drawing from original surveys, survey experiments, and novel field experiments, Donghyun Danny Choi, Mathias Poertner, and Nicholas Sambanis show that although prejudice against immigrants is often driven by differences in traits such as appearance and religious practice, the suppression of such differences does not constitute the only path to integration. Instead, the authors demonstrate that similarities in ideas and value systems can serve as the foundation for a common identity, based on a shared concept of citizenship, overcoming the perceived social distance between natives and immigrants.

Addressing one of the most pressing challenges of our time, Native Bias offers an original framework for understanding anti-immigrant discrimination and the processes through which it can be overcome.

À propos de l?auteur

Donghyun Danny Choi is assistant professor of political science at Brown University. Mathias Poertner is assistant professor of political science at the London School of Economics and Political Science. Nicholas Sambanis is Presidential Distinguished Professor of Political Science and director of the Identity & Conflict Lab at the University of Pennsylvania.