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Socio-Demographic Correlates of Fear of Crime and the Social Context of Contemporary Urban China

  • Original Paper
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American Journal of Community Psychology

Abstract

Previous research in the West has established major socio-demographic correlates of fear of crime. The interpretation of these correlates is typically based on the concept of physical or social vulnerability of individuals. These correlates are implicitly regarded as invariant to social or community contexts, reflecting universal human behavioral patterns. The present study argues that social change may alter patterns of perceptions associated with fear among socio-demographic groups, thus affecting socio-demographic correlates of fear of crime. We explore how social changes in China have created a generational gap that influences the effects of age and education on fear of crime. The study finds that, in contrast with the well-established patterns in Western communities, the young and educated exhibit a higher level of fear of crime in urban China than their counterparts. The study also finds that consistent with Western literature, females are fearful and that personal victimization experience increases the level of fear. We discuss the social and community processes that produce these interesting patterns.

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Notes

  1. Wittebrood (2002) also employs a multilevel framework in the analysis of fear of crime using data for 16 Western industrialized nations from the International Crime Victims Survey (ICVS). Her results for individual-level variables are consistent with those widely observed in studies based on individual nations. Females, the elderly, and those with low SES exhibit high levels of fear. No significant effects are observed for contextual variables, which may reflect the fact that these are measured at the level of the nation. This may be too high a level of aggregation to capture the socially meaningful context.

  2. We are grateful to an anonymous reviewer for suggesting these alternative hypotheses.

  3. This description of Tianjin is taken from the government statistics published online at http://www.stats-tj.gov.cn/2006nj/2/2-2.htm.

  4. We are especially grateful to Zhou Lu, former Director of Crime Research at the Tianjin Academy of Social Sciences, for his expert assistance with all major phases of the research.

  5. Although the questionnaire item does not appear to mention crime specifically, respondents know that the purpose of the survey is to study criminal victimization, and the context implies that the answer refers to fear of crime. Similar measures of fear of crime have long been used in the Western literature (e.g. Hindelang et al. 1978: 176).

  6. Several studies in the West report that past victimization predicts fear of crime (Braungart et al. 1980; Garofalo 1979; Skogan and Maxfield 1981), but other studies cast doubt on this conclusion (Baumer 1985; Hindelang et al. 1978; McGarrell and Giacomazzi 1997; Gates and Rohe 1987; Liska et al. 1988; Garofalo and Laub 1978; Quann and Hung 2002). Cross-national comparisons also indicate that while victimization tends to be associated with fear of crime in different nations, the strength of the association is variable (Quann and Hung 2002). These findings suggest that the correlation between victimization and fear of crime may be conditioned by the larger cultural context (Murck 1997).

  7. We also calculated the intra-class correlation for the unconditional model. It is 0.03, suggesting that the size of the clustering effects over 50 neighborhoods on average is not large, even though the variation of perceived disorder across the neighborhoods is statistically significant.

  8. Our interpretation here assumes that self-assessments of vulnerability might exert a causal inference on perceptions of disorder. A reverse causal process is plausible on logical grounds for self-defense/alertness. Perceiving the neighborhood to be disorderly might stimulate residents to develop the capacity for alertness. As noted, the coefficients for the vulnerability measures are non-significant.

  9. We performed Hausman (1978) tests for the statistical significance of the differences in coefficients across Models 2 and 3 for “income” and “young.” Both differences are statistically significant.

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Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No. 0351014. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. Southwest University of Political Science and Law, Chongqing, China

    Jianhong Liu

  2. Faculty of Social Sciences and Humanities, University of Macau, Av. Padre Tomas Pereira, S. J. Taipa, Macau, China

    Jianhong Liu

  3. Department of Sociology, University at Albany, SUNY, Albany, NY, USA

    Steven F. Messner & Yue Zhuo

  4. Department of Behavioral Sciences, Saint Francis University, Loretto, PA, USA

    Lening Zhang

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  1. Jianhong Liu
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Appendix

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Table 3 Descriptive statistics for variables
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Liu, J., Messner, S.F., Zhang, L. et al. Socio-Demographic Correlates of Fear of Crime and the Social Context of Contemporary Urban China. Am J Community Psychol 44, 93–108 (2009). https://doi.org/10.1007/s10464-009-9255-7

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