The term “hate crime”, existing as a legal concept for approximately 30 years, designates the criminal offence which is motivated (at least partially) by the offender’s prejudice or bias toward the victim’s racial, ethnic, gender, sexual identity, or other social group membership. Even though this term is well-known in the contemporary law practice, and the majority of states eventually enacted the hate crime legislation, there many ambiguous aspects, related to the bias-motivated crimes. In this paper, four articles will be examined as the representatives of particular hate crime problems. Based on that critical analysis, the personal opinion and the conclusion will be given.
How “Hate” Impacts on the Crime Clearance
First of all, it is essential to observe the correlation between the bias-motivated crimes, being the relatively new division of the criminal law, and the standard crimes concerning the crime clearance. Therefore, in the first section of this paper, “The Difference “Hate” Makes in Clearing Crime: An Event History Analysis of Incident Factors” by Lyons and Roberts (2014) will be considered in order to define the crucial factors which affect the clearance of the hate crimes. The authors attempt to draw the differences between bias and non-bias crimes because the same factors can influence the clearance rates differently. In that context, Lyons and Roberts (2014) mention both advantages and disadvantages of investigating the hate crimes. On the one hand, such crimes attract more significant attention since they pose more damage and threat to the community. However, the victim devaluation, based on its commonly low social status, leads to the diminishing of the investigative effort (Lyons and Roberts, 2014, p. 271-273).
In their study, the authors employ the data from the National Incident-Based Reporting System (NIBRS), which is “the largest scale incident-level data set”, in order to examine “differences in clearance by arrest between bias and nonbias violent incidents” (Lyons and Roberts, 2014, p. 273-274). Also, the hate crimes are disaggregated by the underlying motivation, which could be racial, ethnic, sexual orientation and disability. To estimate the given data more accurately, the authors use the event history method of analysis. Time to clearance was chosen as the dependable variable. The independent variables are the bias motivation of different kind, the weapon type, the victim-offender relationship, the seriousness of the case according to the legal offence category, and the demographic characteristics, including gender, race, and age.
The principal conclusion that derives from the authors’ analysis is the fact that bias-motivated crimes are about 9,5% less likely to clear than the conventional crimes. It could designate the additional hurdles and disadvantages of investigating hate crimes that the police encounter. However, when the mentioned category is disaggregated by the bias motivation, it provides a possibility for clarification. Such disaggregation reveals the fact that “only non-race and non-ethnic hate crimes are less likely to clear”, which means that only racial motivation is perceived as deserving the investigative effort (Lyons and Roberts, 2014, p. 283). Additionally, the authors mention that an incident will receive the public attention if it fits the popular conception of the hate crime, which is the White-on-non-White crime, motivated by racial or ethnic bias.
Racism on College Campuses
The second article under analysis, “Dangerous Climates: Factors Associated With Variation in Racist Hate Crimes on College Campuses”, focuses on the racial hate crimes in the context of the college campuses. The authors start their study with the observation that very little attempt was made to explore and systemize the causes of the racial bias crimes in the environment of colleges and schools. Educational institutions endeavour to increase their ethnic diversity, which often brings the negative consequences. The article is one of the first attempts to analyze the influence of the social context of bias crimes.
The authors constitute their research by the theories of ethnic competition and defended neighbourhood. The theory of ethnic competition suggests that the increase in minority population can be perceived as a threat to the dominant group’s welfare. Van Dyke and Tester (2014) observe that “real or perceived ethnic competition may occur on a college campus” (p. 293). It could be coupled with the economic competition for the scholarships, or in the case of a tuition increase. Therefore, the authors presume that the probability of racial bias crimes is higher on predominantly White campuses. Further, the defended neighbourhood theory assumes that the growth of minority population could be embraced as a menace to the predominant cultural identity. Additionally, the authors consider that the presence and the amount of fraternities is also a crucial factor, shaping the campus’ climate.
In the given research, two principal data sources are used: FBI’s 2002 Uniform Crime Report, and the college characteristic data from the National Center for Education Statistics (NCES). The information is analyzed on the basis of numerous variables. A dependent variable is a total number of bias-motivated crimes in 2002, which includes not only racial hate crimes but also the other varieties reported by the colleges. The independent variables are demographics and economic conditions of the campus population, the presence of the fraternity system, and the number of other reported bias crimes. The applied method is the negative binomial regression, which is primarily used in such studies.
As a result, one of the authors’ assumptions did not prove itself: the economic competition was not influencing the development of the racial conflict. However, the other hypotheses were confirmed by the facts of the research. As it was presumed, predominantly White campuses appeared to be the place of more frequent racial conflicts. Also, the small minority population (primarily from 9% to 17%) caused the increase of hate crimes (Van Dyke and Tester, 2014, p. 301). Additionally, as it was also assumed, the presence of the fraternity system enhanced the adverse racial climate. Reporting of other bias-motivated crimes indicated the higher overall number of the hate crimes, reported by the particular college; and the other variables eventually brought no significance to the study.
Correlation between Discrimination and Mental Health
The next two sections will be devoted to a less developed field of study in hate crimes – the discrimination against gays, lesbians and bisexuals (LGB). In this particular section, the article “Discrimination and Mental Health Among Lesbian, Gay, and Bisexual Adults in the United States” by Bostwick, Boyd, Hughes, West, & McCabe (2014) will be examined. The authors posit that LGB community is more exposed to different mental health disparities due to the discrimination. However, little attempt was made to elaborate on the correlation between those factors. According to Meyer’s minority stress model which the authors mention, “health disparities among minority groups are best understood as arising from multiple contextual factors” (Bostwick et al., 2014, p. 37). The importance of the article comprises three critical aspects: (1) the authors focus primarily on the discrimination of LGB community, (2) they study different types of discrimination in complex relations, not only as single phenomena, and (3) it is one of the first research to dwell upon the bisexual discrimination as a distinct type of oppression.
The authors’ analysis is based upon the data from National Epidemiologic Survey of Alcohol and Related Conditions (NESARC). Information for NESARC is collected during the personal interviews, and it represents the non-institutionalized citizens older than 20 years. There are two principal measures of the study: past year discrimination and past year mental health disorders. Past year discrimination is measured by the respondents’ answering on six questions about the different forms of discrimination. As it was mentioned, the authors not only study the individual types of discrimination: they propose three categories to evaluate the interactions between different kinds of discrimination. Past year mental health disorders are measured by the Alcohol Use Disorder and Associated Disabilities DSM-IV Interview Schedule (AUDADIS-IV). The crucial parameters which define the sexual minority subsample are the relations between the dependent variable (any past year mental health disparity) and the independent variables: discrimination, sex and sexual identity, race, age, and income.
As a result, the authors come to several essential conclusions. First of all, their study shows that discrimination, based on sexual orientation or race alone, was not associated with the higher probability of mental health disparities. Only gender discrimination alone produced such effect. However, when two or three types of discrimination were combined, the likelihood of mental disorders increased immensely (Bostwick et al., 2014, p. 43). It is important to notice that there are some limitations for this research: only the sex minorities were asked; NESARC did not give the causal order for answers; past year frame could miss the complete information about the discrimination or the mental disorders.
Spatial Factors in Discrimination
In addition to the previous article’s theme, it is possible to notice that another unexplored factor of sexual minority discrimination is the place of residency. As it is observed in “Region, Social Identities, and Disclosure Practices…” by Swank, Fahs, & Frost (2013), little attention is paid to the macro and structural element in the discrimination analysis, and even less attention is given to the influence of the spatial factor. Another poorly elaborated aspect of that problem is the conditions after the disclosure of one’s sexual orientation vastly vary, depending on the place of residency.
Before the authors begin their research, they provide a relatively broad overview of the literature, concepts, and ideas, related to the principal issue of the article. First of all, they dwell upon the comparison of urban and rural circumstances. Due to such factors as higher level of education and higher social diversity, the civic society is more likely to be tolerant of alternative views and lifestyles. On the opposite, rural dwellers tend to be a lot more conservative, and the authors especially notice the religious conservatism of the Southern areas. Therefore, discrimination is less in the urban circumstances, but, somehow, there are studies which do not approve such conclusion. Another important observation is that living in the same area does not mean the same level of exposure to heterosexism and discrimination (Swank et al., 2013).
The study itself is based on the sample of 285 participants, who were asked different questions through the anonymous survey on the Internet. The e-mails of the participants were found on the listservs for the LGB people. The measures were primarily based upon the six forms of the enacted stigma (similar to the previous research). Other factors that modified the outcomes were the questions about the participant’s location (variables of rural area, small town, midsize city, suburban metropolitan, or central city metropolitan), gender, race, income, and the level of disclosure.
One of the significant results of the study is the connection between the residence in the rural area and the exposure to a higher level of heterosexism and discrimination. Also, it was observed that disclosure of one’s sexual identity increased the amount of bias dramatically. Furthermore, the social inequality factors, such as race and the level of income, influenced by the exposure to heterosexism. Additionally, the authors comment upon the concealment of one’s sexual identity, stating that even though the disclosure can cause complementary trouble, the concealment is often more destructive for the personality (Swank et al., 2013, p. 254). However, the study has a principal flaw: the sample is extremely small, which makes it impossible to come to the broader conclusions. Nevertheless, this research is highly significant due to its innovative field of study.
Personal Opinion on the Subject Matter
In my opinion, each of the four articles under discussion represents a principal aspect of the problem of hate crimes in the United States. I chose the pieces so they could be contingently divided into two fields of study: the racial and the sexual identity bias motivation. I perceive those two themes as the most important to elaborate on. The hate crime law needs a further establishing in the U.S. legislation system for a better police performance, and the colleges should be in a higher control of their racial climate. Furthermore, the oppression of the sexual minorities is also an essential part of the discussion because such abuse provokes mental health disparities among the discriminated groups. Additionally, little attention is paid to investigating the spatial factors, influencing the sexual minority community.
Conclusion
In this paper, the critical analysis of the four scholarly articles was given. Each of the pieces represented a particular aspect of the hate crime problem in the United States. Several conclusions could be made based on that analysis. First of all, the bias-motivated crime law needs further development and elaboration to achieve better investigative results.Secondly, educational institutions’ racial and ethnic policies should be treated with more significant attention. Moreover, the particular consideration should be paid to the mental health disparities of the oppressed minorities and their spatial circumstances. As this paper is a brief descriptive overview of the hate crime issues, future elaboration is needed.
References
Bostwick, W. B., Boyd, C. J., Hughes, T. L., West, B. T., & McCabe, S. E. (2014). Discrimination and mental health among lesbian, gay, and bisexual adults in the United States. American Journal of Orthopsychiatry, 84(1), 35-45.
Lyons, C. J., & Roberts, A. (2014). The difference “hate” makes in clearing crime: An event history analysis of incident factors. Journal of contemporary criminal justice, 30(3), 268-289.
Swank, E., Fahs, B., & Frost, D. M. (2013). Region, social identities, and disclosure practices as predictors of heterosexist discrimination against sexual minorities in the United States. Sociological Inquiry, 83(2), 238-258.
Van Dyke, N., & Tester, G. (2014). Dangerous climates: Factors associated with variation in racist hate crimes on college campuses. Journal of Contemporary Criminal Justice, 30(3), 290-309.