1 / 16

Measuring Delinquency

Measuring Delinquency. CRIM 302. Sources for Measuring Crime & Delinquency. Official Data=Archived data held by an institution or agency Examples: Uniform Crime Reports, Juvenile Court Data Self-Report Data=Information received from the subjects under study

isra
Download Presentation

Measuring Delinquency

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Measuring Delinquency CRIM 302

  2. Sources for Measuring Crime & Delinquency • Official Data=Archived data held by an institution or agency • Examples: Uniform Crime Reports, Juvenile Court Data • Self-Report Data=Information received from the subjects under study • Self-Reported Victimization: National Crime Victimization Survey • Self-Reported Delinquency: National Youth Survey

  3. Ways of Measuring Crime & Delinquency • Raw Numbers: Simple count of individual events • Rates: Sum of Individual Events Compared to Population at Large No. of Crimes * 100,000=# Crimes/100,000 in population No. of People in Population • Allows for accurate comparison across groups, locations, etc. • Percent Change: Proportion of change in individual events from one time to another T2-T1 * 100%= % Percent change from Time 1 to Time 2 T1

  4. Computation Examples • 5000 crimes committed in community of 500,000 people • (500/500,000) * 100,000 • .001 *100,000 • 100 crimes/100,000 people • Or .001*1000=1 crime/1000 people • Crime in 2002=1000; crime in 2003=500 • ((500-1000)/1000) *100% • (-500/1000)*100% • (-.5) *100%=50% decrease in crime

  5. Interpreting the Numbers • Tyranny of small numbers • Small increase in small numbers results in large percentage increases • 100 crimes • 10 juveniles +7  Increase 70% • 90 adults  +45  Increase 50% • Impact of crime and actual nature of the trend can be easily exaggerated

  6. Other Misleading Uses of Data • Long-term trends v. short-term trend • Short-term increase may not be dramatic if viewed in the long-term • Comparisons • Using the lowest points as a base year for comparison • Not using a comparison group

  7. Official Data: Uniform Crime Reports • The Federal Bureau of Investigation (FBI) began collecting data from law enforcement agencies on number of crimes reported to police in 1929 • The UCR covers over 95% of the United States and reports: • No. of Crimes Reported to Police • No. & characteristics of Offenders Arrested • No. of Crimes Cleared by Police • Additional Information Provided about Homicide, Police Department Characteristics, Crime Consequences

  8. Substance of the UCR • UCR represents one of two primary measures of crime trends for the U.S. • Index and Non-Index Crimes • Index Crimes Partitioned into 2 Parts • Violent Crimes: Murder/Manslaughter; Aggravated Assault; Robbery; Rape • Property Crimes: Burglary, Motor Vehicle Theft, Larceny, Arson • http://www.fbi.gov/ucr/ucr.htm

  9. Strengths • Best measure of crime across the nation that we currently have • Validity for certain crimes • Problems tend to be stable over time, allowing trends and patterns to surface • Easy to access and inexpensive • Allows for city and regional trend comparisons • Provides detailed information on reporting patterns, who is arrested, and homicides

  10. Weaknesses • Doesn’t capture unreported crime--validity • Only most serious crime is reported • Does not include federal offenses • No. arrested is not equal to the actual number of youths who committed crime—group arrests overestimate juvenile crime • UCR is based on summary data that does not allow closer inspection into each arrest • Quality of data questionable: • Underreporting/overreporting by law enforcement • Variability of police practices/Use of arrest

  11. Future of the UCR • The National Incident-Based Reporting System • Launched by the FBI in 1988 for eventual replacement of the Uniform Crime Reports system • Collects a wide range of information on victims, offenders, and circumstances for more offenses than the UCR • Offenses tracked in NIBRS include violent crimes (e.g., homicide, assault, rape, robbery), property crimes (e.g., theft, arson, vandalism, fraud, embezzlement), and crimes against society (e.g., drug offenses, gambling, prostitution). • Collects information on multiple victims, multiple offenders, and multiple crimes that may be part of the same episode. • Not yet representative across the country—In 1997, 12 States were participating

  12. Victimization • Two primary sources of data: National Crime Victimization Survey and the National Incident-Based Reporting System • The National Crime Victimization Survey (NCVS) • Victim self-report survey conducted by the U.S. Department of Commerce, Bureau of the Census on behalf of the U.S. Department of Justice, Bureau of Justice Statistics for the past 20 years • Data obtained from a nationally representative sample of roughly 43,000 households comprising nearly 100,000 persons • Remain in sample for 3 years • Interviewed every 6 months • All individuals 12 and older are interviewed about the frequency, characteristics and consequences of criminal victimizations they experienced within a particular time frame • Examines the following crimes: Rape, sexual assault, robbery, assault, theft, household burglary, and motor vehicle theft • Use data to compare with UCR trends as well as estimate the likelihood of victimization for the population and segments of the population (e.g., women, the elderly, members of various racial groups, city dwellers, or other groups) • http://www.ojp.usdoj.gov/bjs/pub/pdf/cv02.pdf • Sources: Finkelhor, D. & Ormrod, R. (2000). Characteristics of Crimes Against Juveniles. Washington, DC: Department of Justice, Office of Juvenile Delinquency & Prevention; National Crime Victimization Survey; National Incident-Based Reporting System

  13. Strengths of NCVS • Allows “check” of UCR (NCVS specific)—measures “dark figure of crime” • Collects a lot of information necessary to understand crime and victimization but not found in official crime reports • Not subject to political agendas (necessarily)

  14. Weaknesses of NCVS & Self-Report • Lying • Exaggeration/Embarrassment • Memory and accurate time period • Cost and accessibility • Hidden Populations or missing populations • Inaccurate information • Administration of the Interview (face to face v. phone) • Refusal rates

  15. Self-Report Data • Monitoring the Future • Random sample of schools • 12th graders in each selected school participate • Sub-sample is followed over time • National Youth Survey: Longitudinal, cohort study of juveniles throughout the teen-age years • Started 1976 with 1725 11-17 year olds who were followed until 1993 (27-33 years old) • Measured delinquency, victimization, and various theoretical variables • Provide much more information about the various relationships • The Youth Development Study • Recent effort to follow cohorts of youth in Richmond, VA, Denver, CO, and Rochester, NY • High-risk youth samples • http://ojjdp.ncjrs.org/ccd/rochester.html

  16. Self-Report Differences • Contrary to arrest rates, there was no sharp increase in violence in self-report data, indicating arrest data may have exaggerated violent crime trend • Attention to the role of enforcement trends, discrimination, and paternalism • More youth commit crime than are arrested • Females commit crime at a rate more similar to males than seen in official statistics • The more delinquent a youth is, the greater the likelihood he/she will be victimized • Socioeconomic status is a better predictor of delinquency than race—the offending differential reduces substantially when SES is accounted for

More Related