309
Views
6
CrossRef citations to date
0
Altmetric
Articles

Perceived risk of crime: A tale of two immigrant groups in Metro Detroit

&
Pages 117-137 | Received 28 Jun 2016, Accepted 09 Dec 2016, Published online: 27 Jan 2017
 

ABSTRACT

A particular source of anxiety for many immigrants is personal safety. This study examines the levels and correlates of perceived risk of crime among two understudied immigrant groups, Arab and Chinese immigrants, who resided in an understudied geographic area, the Detroit metropolitan area. Results suggested several universal and immigrants-specific correlates that are significant predictors of Arab and/or Chinese immigrants' perceptions of crime, including self-defense ability, police effectiveness, neighborhood collective efficacy, language proficiency, expectation of U.S. crime condition prior to arrival, and perception of home society crime. Implications for future research are discussed.

Acknowledgments

This work was supported by the National Institute of Justice (NIJ), Office of Justice Programs, U.S. Department of Justice under Award No. 2013-IJ-CX-0020, and by Wayne State University (WSU) under the University Research Grant. Points of view are those of the authors and do not necessarily represent the view of the NIJ or WSU. The authors would like to thank Charles Klahm for his helpful input on this article.

Notes on contributors

Yuning Wu and Jennifer Wareham are both Associate Professors in the Department of Criminal Justice at Wayne State University.

Notes

1. This study treats Asian and Arab immigrants as two aggregated ethnic groups, which although follows official definition and academic tradition, fails to uncover the potential attitudinal variations within Asian and Arab immigrant populations. Indeed, though many Asians and Arabs share common cultural traditions and values, both are not entirely homogeneous and have very diverse subgroups within.

2. We will discuss further the value of comparing Chinese and Arab immigrants in the literature review section.

3. In the early 1900s, for the purpose of citizenship and associated rights, Arab Americans fought for the racial classification of “white”, and were eventually defined as white by law since 1944. However, in the 1980s and 1990s, many Arab Americans began to fight for changing identity markers. As Kayyali (Citation2013, p. 1299) observed, “the rise of multiculturalism and ethnic pride, combined with influxes of new, more diverse immigrants, has created large segments of Arab Americans who do not feel ‘white’ and who perceive themselves as persons of color.” Recognizing this trend of identity shift, the United States Bureau of the Census has proposed a standalone “Middle Eastern or North African” (“MENA”) box for the 2020 census. This change, if implemented, offers Arab Americans the opportunity to identify as MENA, and nonwhite (Beydoun, Citation2015).

4. Sampson and colleagues (1997) defined collective efficacy as “social cohesion among neighbors combined with their willingness to intervene on behalf of the common good” (p. 918). Their study found that neighborhood stratification (indicated by concentrated disadvantage, immigration concentration, and residential stability) can be linked to lower levels of collective efficacy, which can in turn be linked to increased violence.

5. Power analysis is a statistical technique that allows one to determine the minimum sample size necessary to detect a given effect size, or the minimum effect size likely to be detected with a given sample size (Cohen, Citation1988).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 299.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.