The vicarious effects of hate: inter-ethnic hate crime in the neighborhood and its consequences for exclusion and anticipated rejection

ABSTRACT

Hate crime victimization is harmful for victims and those who share the victim’s identity. It may also be harmful for the broader community. Yet, few studies focus on the ripple effects of hate. This paper examines how secondary exposure to hate crime in the neighborhood, through witnessing or hearing about hate crime, influences individual perceptions of ethnic minorities, which in turn can harm social relations. Findings reveal that those who witness hate crime express greater anger towards ethnic minorities. Those who rely on second-hand information about hate crime in the community are more likely to anticipate rejection on the basis of their ethnicity, hold negative attitudes towards ethnic migrants and intend to take actions to exclude new migrants from their communities when compared to those who do not have such information. These findings have implications for community cohesion in multi-ethnic neighborhoods.

KEYWORDS:

• Hate crime
• community cohesion
• social exclusion
• vicarious effects
• victimization
• anticipated rejection

Acknowledgements

The authors would like to thank the partners from Monash University, Deakin University, Australian Catholic University and the Australian Multicultural Foundation who participated in the project that provided the data used for this paper. The authors would also like to thank the anonymous reviewers for their useful feedback.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 A participant that has witnessed an event, and heard about an event are categorised as witnessed. Nine participants have witnessed an attack but did not report hearing about an attack, and 52 participants have witnessed harassment but not heard about it.

2 Our final sample is skewed towards women, older people (aged 45–64), Australian-born and university-educated residents. We therefore created a series of weights to use in individual level analyses to bring the achieved respondent profile into line with ABS demographic indicators for the general population of the Melbourne Greater Capital City Statistical Area (GCCSA). Weighting was calculated to account for four factors: age, sex, place of birth and education.

3 Supplementary analysis was run using linguistic diversity as a measure, there was no significant variation in the results. Analysis available upon request.

4 The latter category contains students.

5 In Australia, there are two main political parties. The Liberal National Party is currently in government, ideologically sits at centre right, and the Labor party sits centre left. The Greens party are a minority party that sit on the left. “Other independent party” is comprised of those who voted for One Nation, Family First, Nick Xenophon Team, Independents and “other”.

6 In line with previous neighborhood research in Australia, we use State Suburb Codes to determine the administrative boundaries from the 2016 Australian Statistical Geography Standards (Wickes et al. 2013).

7 We used the Blau index (Blau 1977) to capture linguistic diversity in line with previous studies of this nature within Australia (Wickes et al. 2013). The Blau index indicates the probability of two randomly selected residents from the same neighborhood speak a different language, the lower the number, the more homogeneous the area.

Additional information

Funding

The authors gratefully acknowledge the Victorian Government's Round 2 Social Cohesion Research Grants Program administered through the Department of Premier and Cabinet.