The Myth of Accurate Crime Measurement (Ch 1)

Today’s myth: Crime measurement is an accurate science, so all crime statistics can be trusted as fact.
The myth is framed as: "Crime statistics are objective truth."
These statistics are relied upon by multiple groups: law enforcement, politicians, media, and the public (us).
They are used to justify budgets, policies, and social fears.

Data do provide estimates of the extent and social distribution of crime.
Several general conclusions can be supported by the data.
However, the absolute volume of crime in the United States cannot be determined.
Differences in methods, population bases, and definitions/rules for counting crime affect comparisons across data sources and time.

Official Data (UCR/NIBRS)
Victimization Surveys (NCVS)
Self-Report Studies
None of these sources are perfect; each has strengths and limitations, and some limitations can be serious.

Uniform Crime Reports began in 1930; replaced by NIBRS (National Incident-Based Reporting System).
Compiled by the FBI from police agencies.
Two stages of data: citizens reporting crime and police responding/recording crime.
Classification includes Part I vs. Part II crimes, which shapes our knowledge and understanding of crime.

UCR uses the Hierarchy Rule; NIBRS does not use this rule.
Not all crimes are reported to police (factors include victim/offender relationship, seriousness, trust in police).
Police may underreport or misclassify crimes, which can distort perceptions of safety, department effectiveness, and policy needs.
Examples include reporting practices under the Clery Act for university crime reporting.
Dark Figure of Crime: Reported Crime vs. Unreported Crime
Graphic shorthand: "Dark Figure of Crime" = the unreported crimes that exist behind the official counts.
Political Uses of Crime Statistics
Crime rates affect funding for criminal justice agencies, elections, and the reputation of cities, universities, departments, and politicians.
Manipulation is common: downgrading offenses, citing unfounded cases, skipping monthly reports, leaving cases open.
Example reference: WI 2022 Senate Ad (Wisconsin Truth PAC).

Began in 1973 as crime was increasing; an annual national survey by the Bureau of Justice Statistics (BJS).
Captures the "dark figure of crime" by surveying victims about crimes whether or not they were reported to the police.
Finds that unreported crime is substantial; less than half of crime is reported to police.
Shows that crime rates reported in UCR/NIBRS are about half of the rates found in NCVS, i.e., NCVS rates are roughly
$ext{NCVS rate} \approx 2 \times \text{police-reported rate}.$

Higher rates observed among low-income populations, non-white populations, and males.
NCVS cannot measure homicide or victimless crimes.
NCVS does not measure white-collar crime.
Respondent issues: memory, bias, sample gaps; how these issues distort results should be considered.

Developed in the 1950s to capture unreported behaviors directly from respondents rather than victims.
Based on survey methods.

General trends in crime are detectable when using multiple data collection methods.
Since the early 1990s, crime has declined overall (with a small blip in 2020).
Most crimes are minor, and most violent crimes are attempts rather than completed violent outcomes (no major injuries in many cases).

White-collar crime is underrepresented:
- Example: theft of $50 from a car is counted; theft of millions by a CEO is not counted in some counts.
Government or state crime is often not captured well.
These omissions can shape public perception of crime and influence policy decisions.

Criminal Justice Agencies: funding, resources, and growth.
Politicians: crime can be a powerful issue in elections.
Incumbents: portraying crime as low makes them look effective; claim of low crime benefits them.
Challengers: portraying higher crime signals a need for new leadership.
Communities and Colleges: safety perceptions influence property values, enrollment, and funding; appearing safer can be economically advantageous.

Gallup data show public perceptions of crime seriousness both nationally and locally over time (2000–2020).
Percentages of respondents rating crime as extremely or very serious have varied, with differences between national and local areas.
These perceptions do not always align with actual crime trends.

Visualization (1993–2014) comparing:
- U.S. violent crime rate (victimizations per 1,000 people per year)
- Americans’ perception of whether crime is up relative to the previous year
Key takeaway: public perception of crime levels often overstates or misreads actual trends in violence.

If the public believes numbers presented by politicians or government or colleges are true, policy directions may be biased by those beliefs.
Consequences include:
- If crime is claimed to be rising, support for punitive policies may grow.
- Stereotypes about criminal groups may be reinforced (e.g., criminals are Black, poor, or immigrants).
- Assertions about “prison works for all crime” can drive policy without solid evidence.
Example: Montana Meth Project – evidence shows no decline in meth use attributable to the ads or the funding; policy outcomes did not align with claims.

Nixon (1971) labeled drug abuse as “public enemy number one.”
At that time, ~2% of the population viewed drugs as a major issue.
Reagan era expanded drug policy due to media coverage of the crack epidemic and rising public concern.
Policy responses included mandatory minimum sentences and a 100:1 sentencing disparity between cocaine and crack.
Result: an unequal increase in incarceration rates for non-violent Black offenders.

Crime data are partial, political, and problematic.
It is important to consider who benefits from these myths and how myths influence citizens and policy.
Better data lead to better policy.
Key question: How should crime statistics be used in policymaking to avoid distortion and injustice?