BCJ 4201, Race and Ethnic Relations 1
Course Learning Outcomes for Unit I
Upon completion of this unit, students should be able to:
6. Discuss the current nationwide reporting system for hate crime data collection.
6.1 Identify the quality of criminal justice data.
6.2 Identify which agency collects the various types of hate crime data.
6.3 Identify current hate crime statistics.
Course/Unit Learning Outcomes
Learning Activity
6.1, 6.2, 6.3
Unit Lesson
Chapter 1
Unit I Assessment
Required Unit Resources
Chapter 1: Race, Ethnicity, and Crime: American’s Continuing Crisis
Unit Lesson
In this unit, you will be introduced to the complicated relationship between race, ethnicity, and the criminal justice system. We begin by considering the difficult task of comprehending the challenges presented by race and ethnicity in the United States. We will also differentiate between disparity and discrimination. Finally, we will look at the recording and reporting of crime from a race and ethnic perspective.
The reading assignment discusses the complexity of studying race and ethnicity, as they are not mutually exclusive categories. Often, an individual does not belong biologically 100% to a single race. Also, ethnic labels applied in the United States are very few but include a wide variety of individuals with complex racial and geographical backgrounds.
Crime Data
Data is essential to understand the various workings of the criminal justice system. Data and statistics are used to identify areas in need of services, to evaluate the effectiveness of programs, and to guide the development of policies (Gau, 2019). Criminological data is frequently used to monitor crime in specific locations or jurisdictions, to develop risk-assessment tools to assist in making decisions about offender treatment, or to identify the need to change policies. Specifically, evidence-based practices have become the primary means of implementing change in criminal justice agencies (Gau, 2019). Through the use of rigorously evaluated data, stakeholders can empirically demonstrate that their policies are effective.
The knowledge gained from data is viewed as objective and consistent. However, the data outcomes are only as good as the data inputs. If the information entered is faulty, the results will not be valid. Therefore, understanding how criminological data is gathered is essential (Gau, 2019).
Crime data is gathered in several methods, including officially recorded and self-reported methods. Officially recorded data is information recorded by official means. Common types of official data include arrests recorded by law enforcement agencies, court records of convictions and sentences, and corrections records regarding admissions and releases. Self-reported data is information provided by individuals about their experiences (Kirk, 2006). As you may have learned in other courses, one of the concerns about using crime data is the “dark figure of crime” (i.e., the portion of crime that occurs but goes unreported). Through the use
UNIT I STUDY GUIDE
Race, Ethnicity, and Crime in America
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of self-reported data, some of the crime unknown by official sources or that dark figure is captured (Schmalleger, 2018).
The Uniform Crime Report (UCR) is the most common source of officially recorded crime data at the national level. The UCR is compiled by the Federal Bureau of Investigation (FBI, 2018d). Local, county, and state law enforcement agencies voluntarily report their offense and arrest data to the FBI. However, it is important to realize that the data is based on the agencies’ participation and method of recording. Agencies may be constrained by time or resources, impacting their ability to report. Also, there is variation in the classification of crimes across jurisdictions. For example, a crime recorded as larceny by one police department may be reported as burglary by another. The UCR contains information on crimes such as murder, robbery, burglary, and arson, as well as several others (FBI, 2018d). While the UCR collects data on the number of offenses reported to the police, the number of arrests, and characteristics of those arrested, it does not measure the characteristics of the victims.
The National Crime Victimization Survey (NCVS) is the most common source of self-reported crime data. The NCVS is collected by the Bureau of Justice Statistics (BJS, 2008) on an annual basis. The survey is distributed to approximately 95,000 U.S. households, capturing approximately 240,000 interviews from 160,000 individuals. These victimization surveys capture a myriad of demographic and relationship information regarding both the victim and the offenders. The surveys also collect particulars of the crime and the frequency of the crime as well as if the incident was reported to officials. The NCVS captures all types of personal and property crimes (BJS, 2008).
Just as the personal categorization of race and ethnicity is confusing, the recording of such information in crime data is difficult. For example, when officers are completing reports, they may not have accurate information or any race or ethnicity information on the victims, witnesses, or suspects. This reporting hindrance is particularly true when the officer does not have access to official information such as a driver’s license or state identification, and many forms of identification do not include ethnicity information. As discussed by Walker et al. (2016), many fall into multiple categories of race and ethnicity, yet forms, identification, and reports allow the option to choose only one or offer a very limited selection.
Hate Crime Data
Hate crimes are criminal activities motived by discrimination on the basis of race, amongst other victim characteristics. The law defines hate crimes as “crimes that manifest evidence of prejudice based on race, religion, sexual orientation” (FBI, 2018a, para. 1). Initially, this law covered bias crimes due to race, color, religion, or nationality. However, in 2009, the Matthew Shepard and James Byrd, Jr., Hate Crimes Prevention Act was passed to expand the law to also include crimes based on bias against another’s gender, gender identity, sexual orientation, or disability (Gerstenfeld, 2017).
For over 30 years, efforts have been made to track hate crimes in the United States. However, the Hate Crime Statistics Act of 1990 applies only to tracking hate crimes at the federal level, and it does not require the reporting of such statistics at the state and local levels. The FBI compiles the data but is reliant on the local agencies to report.
Both the UCR and the NCVS compile information on hate crimes. According to the UCR for 2017, 8,427 incidents of hate crime were reported. This number was an increase of almost 17% from 2016 (FBI, 2018c). Over half (58.1%) of those were considered to be motivated by bias against the victim’s race or ethnicity. The majority of these crimes were crimes against persons (60.3%), and of those, intimidation was the most frequently reported crime at 44.9% (FBI, 2017; FBI, 2018c).
Of hate crimes against property, an overwhelming majority (74.6%) were crimes including destruction, damage, and/or vandalism (U.S. Department of Justice 2018a). The difficulty in classifying crimes as hate crimes is a requirement for law enforcement to identify the motivation of the offender (FBI, 2018b). Additionally, it is estimated that approximately less than one-third of hate crimes are even reported to the police (Gerstenfeld, 2017).
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Comparatively, the BJS also acquires information regarding hate-based crimes in the NCVS. The identification of the offender’s motivation is based on the victim’s perception. However, the NCVS provides specific indicators that must be present to classify an incident as a hate crime.
According to the BJS (2011), a crime is classified as a hate crime in the NCVS when the victim report shows one of three types of evidence that the act was motivated by hate, which are listed below.
1. The offender used hate language.
2. The offender left behind hate symbols.
3. Police investigators confirmed that the incident was a hate crime.
According to the Masucci and Langton (2017), between 2004 and 2015, there was a yearly average of 250,000 hate crime victimizations in the United States, most of which were not reported to the police. Similar to the UCR data, the NCVS reports that for the years 2011–2015, the majority of hate crimes were based on race (48%) or ethnic (35%) biases. According to the NCVS (as cited in Masucci and Langton, 2017), for the years 2011–2015, Hispanics reported higher rates of violent hate crimes than either non-Hispanic Whites or African Americans.
Figure 1: UCR
Figure 1: UCR –– Bias motivation cateBias motivation categories for singlegories for single–bias ibias incidents in 2017ncidents in 2017
(FBI,
(FBI, 20182018a)a)
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Research indicates that most hate crime offenders share similar characteristics. Generally, perpetrators of hate crimes are young, White males in their late teens or early 20s. Typically, they have no prior arrests and may offend in small groups of friends. It is believed that many are motivated by excitement or peer pressure rather than true hate (Gerstenfeld, 2017).
Looking Forward
The U.S. Department of Justice hosted a Hate Crimes Summit, which convened in June 2017, to address numerous issues surrounding hate crimes, some of which included reporting. The Hate Crimes Coalition made recommendations to the U.S. Attorney General to create a government-sourced website to provide statistics and resources regarding hate crimes to improve the collection of hate crime data by incentivizing and training law enforcement agencies. Other recommendations were made to research the underlying issues prohibiting victims from reporting hate-based crimes and the barriers to agency reporting (Hate Crimes Coalition, 2017). Since the summit, the U.S. Department of Justice (2018b) has made efforts to meet these recommendations. In October of 2018, the U.S. Department of Justice launched a Hate Crimes website to provide data, information, and resources for citizens and agencies.
Understanding the importance of data as well as the variety of methods in which it is gathered allows us to be more informed of the world around us. Comprehension of statistics provides the ability to be more discerning of the news that we read and the information that we hear, allowing us to interpret for ourselves their meaning. Finally, as you navigate your criminal justice career, comprehension of data and statistics enhances your ability to provide recommendations and solutions to the needs of your agency.
Figure 2: NCVS: Violent hate crime victimization reported
Figure 2: NCVS: Violent hate crime victimization reported and not rand not reported to eported to ppolice, 2004olice, 2004––20152015
(Masucci & Langton, 2017)
(Masucci & Langton, 2017)
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References
Bureau of Justice Statistics. (2008). Data collection: National Crime Victimization Survey (NCVS). Office of Justice Programs. https://www.bjs.gov/index.cfm?ty=dcdetail&iid=245
Bureau of Justice Statistics. (2011). Hate crime. Office of Justice Programs. https://www.bjs.gov/index.cfm?ty=tp&tid=37
Federal Bureau of Investigation. (2017). Table 2: Incidents, offenses, victims, and known offenders. https://ucr.fbi.gov/hate-crime/2017/tables/table-2.xls
Federal Bureau of Investigation. (2018a). About hate crime statistics. https://ucr.fbi.gov/hate-crime/2017/resource-pages/about-hate-crime
Federal Bureau of Investigation. (2018b). Methodology. https://ucr.fbi.gov/hate-crime/2017/resource-pages/methodology
Federal Bureau of Investigations. (2018c). 2017 Hate crime statistics released: Report shows more departments reporting hate crime statistics. https://www.fbi.gov/news/stories/2017-hate-crime-statistics-released-111318
Federal Bureau of Investigation. (2018d). Uniform Crime Reporting (UCR) Program. https://www.fbi.gov/services/cjis/ucr/
Gau, J. M. (2019). Statistics for criminology and criminal justice (3rd ed.). Sage.
Gerstenfeld, P. B. (2017). Hate crime. In P. Sturmey (Ed.), The Wiley handbook of violence and aggression. Wiley-Blackwell.
Hate Crimes Coalition. (2017, September 15). Hate Crimes Coalition policy recommendations [Letter to John M. Gore]. Anti-Defamation League. https://www.adl.org/sites/default/files/documents/final-post-Charlottesville-DoJ-hate-crime-summit-coalition-recommendations.docx.pdf
Kirk, D. S. (2006). Examining the divergence across self-report and official data sources on inferences about the adolescent life-course of crime. Journal of Quantitative Criminology, 22(2), 107–129. https://link.springer.com/article/10.1007/s10940-006-9004-0
Masucci, M, & Langton, L. (2017). Hate crime victimization, 2004-2015 [Special Report No. NCJ 250653]. U.S. Department of Justice. https://www.bjs.gov/content/pub/pdf/hcv0415.pdf
Schmalleger, F. (2018). Criminal justice: A brief introduction (12th ed.). Pearson.
U.S. Department of Justice. (2018a). FBI releases 2017 hate crime statistics. https://www.justice.gov/hatecrimes/hate-crime-statistics
U.S. Department of Justice. (2018b, October 29). Justice Department releases update on hate crimes prosecutions and announces launch of new hate crimes website [Press release]. https://www.justice.gov/opa/pr/justice-department-releases-update-hate-crimes-prosecutions-and-announces-launch-new-hate
Walker, S., Spohn, C. C., & DeLone, M. (2016). The color of justice: Race, ethnicity, and crime in America (6th ed.). Cengage Learning.
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Suggested Unit Resources
In order to access the following resources, click the links below.
The chapter from the textbook is also presented as a PowerPoint presentation and as a visual summary through MindTap.
Click any of the links below to access an alternative format.
• Chapter 1 PowerPoint Presentation
• PDF version of the Chapter 1 PowerPoint Presentation
The following Visual Summary can be viewed in MindTap through clicking on the link provided in the Unit I tab in Blackboard.
• Chapter 1 Visual Summary
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