Class Notes (807,356)
United States (312,498)
CRJU 20423 (22)
Merken (22)
Lecture 3

CRJU 20423 Lecture 3: Chapter 3 - When Crime Waves Premium

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School
Texas Christian University
Department
Criminal Justice
Course
CRJU 20423
Professor
Merken
Semester
Spring

Description
Chapter 3: Crime Waves by the Numbers Statistics matter, encourage their perspectives and ideas about crime; get it from the media; it is easy to get information from the media, you just have to listen Three things viewers want to know about a crime: 1) if crime is increasing, 2) decreasing, 3) if it is happening around them Innumeracy and Number Numbness Innumeracy illiteracy of numbers; dont know how statistics are collected, generated, how they are interpreted Number Numbness inability to understand large or small numbers in statistics; we do not understand and think of the worse Why its a problem and why we are having issues with innumeracy Lack of rigorous mathematical education in schools Loud and proud about inability of understanding statistics Mathematics = impersonal, not fun, not emotional or full of drama or excitement, no opinions Statistics in the Raw Incidents occurring in succession; changes our perspective of what is actually going on Worsening Effect if individuals look at crimes and see that a particular one is declining, they are upset that it isnt eliminated Crime Clock Issues we cannot look at population changepopulation demographic; cant use number of seconds to determined; raw data numbers that have not been processed to be used **Emergent Crime Problems Established have culture or legal history; been around for a long time (murder, rape, theft, kidnapping, robbery) Emergent new; cybercrime, identity theft, carjacking, road rage, home invasion Problem: statistical data does not exist the guessing game Jenkins (1994) and the Serial Killer Crime Wave you cant contribute victim to serial killer Large numbers = puts issue on agenda and keeps issue in the forefront Statistical Record Keeping = Social Process Interpretation of a crime is key in terms of looking at a type of crime; skew data Misinterpretation of a crime; think a crime happened to them but it did not or think a crime didnt happen to them and it actually did Redefinitions of crime (theft, vandalism, stalking) interpretation of crime is going to be different from person to person Tolerance of a crime viewed differently Manipulation of statistical data Funding, universities, public impression
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