Replication Data for Proportional Immigration Enforcement
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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/ZFOTRO
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资源简介:
This article considers how much harm is justified in reaching a given immigration goal. Political philosophers generally overlook this question, focusing on whether states have a right to exclude immigrants in general, rather than whether certain means of exclusion are justified. For example, even if excluding new migrants during a pandemic is justified, shooting at migrants attempting to enter is likely an unjustified means of exclusion. We argue harm against migrants in immigration enforcement must be proportional. Whether harm is proportional is impacted by the level of harm migrants experience relative to the harm immigration control averts; whether migrants are forced to migrate; whether the harm against migrants is intended; and whether the harm is instigated directly by a state vs. a non-state actor. We demonstrate that these claims regarding enforcement have implications for justice in immigration currently overlooked. Moreover, these claims are supported in a sample of citizens of the UK and US, despite general opposition to increasing migration in both countries. Drawing on an original experiment focusing on enforcement, novel in evaluating whether the public's opinions are consistent with the requirements of immigration justice, we demonstrate that opinions on enforcement are consistent with sub-principles of proportionality we present.
提供机构:
Harvard Dataverse
创建时间:
2022-10-05



