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Casting a crime net, catching immigrants : an analysis of secure communities' effects on the size of foreign-born Mexican populations

Following the precedent decision to expand the power of immigration enforcement set by the Immigration and Nationality Act Section 287(g), the Department of Homeland Security developed its own partnership agreement with local police to increase detection and deportation efforts through its 2008 policy, Secure Communities (S-Comm). S-Comm represents the nation’s “largest expansion of local involvement in immigration enforcement in the nation’s history” (Cox & Miles 2013, pg. 93). Although slated to enhance public safety by removing “criminal aliens” convicted of serious offenses, S-Comm has broaden its scope to achieve attrition in the undocumented immigrant population more generally by also focusing on the removal of those who violate low-level and immigration laws, as well as those who have recently entered the U.S. illegally. Its implementation and enforcement procedures, however, have been found to disproportionately target foreign-born Mexican residents relative to other undocumented individuals, which may lead to negative consequences for S-Comm’s efficacy. Has S-Comm effectively reduced the size of the Mexican immigrant population in the U.S.? Exploiting the variation in the timing of its implementation as well as the disparate levels of its enforcement, my research extends a quasi-experimental design to investigate S-Comm’s effect on the size of local Mexican immigrant populations. Testing the influence of S-Comm’s implementation and enforcement will reveal the salience of passing laws that target unauthorized migration—an empirical contribution to previous work that has only assessed state and local policies. Moreover, such results may also enhance theoretical knowledge of punitive practices formulated to produce deterrence. / text

Identiferoai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/23652
Date25 March 2014
CreatorsGutierrez, Carmen Marie
Source SetsUniversity of Texas
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf

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