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FSU CCJ 4700 - Measuring crime

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CCJ4700Exam 2 ReviewMeasuring crime- Uniform Crime Reporting Program - purpose- provide uniform definitions of crime- data collection- content of the data source- part I offenses (index)- murder; rape; robbery; aggravated assault; burglary; larceny; MVT; *arson- added in 1979- most likely to be reported- can determine that a crime occurred- occur in all areas- occur with frequency- serious crimes- 2 different indexes- violent crime index: homicide; rape; robbery; aggravated assault- property crime index: burglary; larceny; MVT- 3 forms of data- crimes known to police- Supplementary Homicide Reports (SHR)- crimes cleared by police- excludes- offender characteristics- victim characteristics- individual-level data- characteristics of every single count of crime- hierarchy rule- if two different crimes happen at one time, only the more serious crime is reported- factors affecting reporting of crime- “reactive mobilization process”- seriousness- e.g. homicide is well reported and larceny in underreported- type of crime- non-reporting- result in “underestimates- factors affecting recording of crime- Organizational pressure- "Crack downs" - Organizational changes - Diff. interpretation - Professionalism - Discretion- acceptable and unacceptable uses of UCR data- acceptable- homicide and auto theft- local agency decisions- trends within units- unacceptableCCJ4700Exam 2 Review- NOT across jurisdictions- one city might report crime more than another- National Crime Victimization Survey - purpose- more reliable estimates- situational factors- where did it occur?- what time of day?- demographic data- victims- offenders- characteristics of both- design- reference period - 6 months- bounding interview - the data does not become part of the tabulations- way of making sure that we are not mistaking what happened in the last 6 months- screening questions - when asking the interviewee about their victimizations; you ask what crimes they were the victim of first, then move on to the details of each - short cues- to deliver as many possible cues in a short period of time by asking them in rapidsuccession to one another- to help prompt memory of incident- telescoping- moving something out or bringing it into the reference period - data content - Part I UCR offenses- same definitions- not homicide- not arson- add simple assault- Criminal Victimization in the United States- victimization estimates- offense estimates- national level- individual level data- demographic variables- victim- offender- situational variables- problems with NCVS- problems with interview- boring- learn to under-reportCCJ4700Exam 2 Review- social desirability- recall problems- people forget details- phone interviews- much less expensive- lower response rate- less valid informationSampling - Chapter 5- population- the entire set of elements in which we are interested- e.g. individuals, cities, states, countries, prisons, schools- sampling frame - list of all possible elements- often hypothetical- can create systematic error- use best approximation- recognize limitations- sampling element - individuals who are selected and interviewed from the sampling frame- sampling ratio- would like to get the biggest sample possible- ration of sample to population- 500 from 50,000: SR = 1 in 100 (1%)- parameter vs. statistic - parameter- characteristic of population- income, average, median- always unknown- statistic- characteristic of sample- estimates the parameter- sampling error - any difference between between the characteristics of a sample and the characteristics of the population from which it was drawn- the larger the sampling error, the less representative the sample is of the population- non-probability sampling- available subjects/haphazard/accidental/convenience sampling - conveniently accessible- people in a mall- people on the street- students in a class- cheap and easy- not representative- useful for pre-testing- purposive/judgmental sampling- specifically selecting certain cases for a reasonCCJ4700Exam 2 Review- based on purpose of study- 3 cases where appropriate- especially informative- study of unusual cases- study of a wide range of cases- snowball sampling- uses sample cases to find more cases- exploratory- quota sampling- match characteristics of population- difficult to know population info- can still be biased- cheaper and easier that probability- be cautious- probability sampling- simple random sampling (SRS) - a method of sampling in which every sample element is selected only on the bias of change, through a random process- compile sampling frame- assign number to each case- use random numbers to select- rarely used in practice- systematic sampling- a method of sampling in which sample elements are selected from a list or from sequen-tial files, with every nth element being selected after the first element is selected ran-domly within the first interval- similar to SRS- sampling interval = population/sample size- potential for systematic bias- stratified sampling- a method of sampling in which sample elements are selected separately from population strata that are identified in advance by the researcher- separate population into “strata”- randomly select within strata- representativeness across strata- “oversampling”- cluster sampling- sampling in which elements are selected in two or more stages, with the first stage being the random selection of naturally occurring clusters and the last stage being the random selection of elements within clusters- cluster = unit containing sampling elements- clusters are randomly selected- smaller clusters randomly selected- advantages- no sampling frame- reduced costCCJ4700Exam 2 Review- disadvantages- increased error at each stage- need enough clusters- randomness- EPSEM- Equal chance of being selected- probability proportionate to size (PPS)- example- 30 out 30,000 colleges- 100 students from each college- college 1- 400 students- chance is 100/400 = 25%- college 2 - 40,000 students- chance is 100/40,000 = .25%- choices to make- interview more at large college?- interview fewer at small college?- make large colleges more likely to be selected- ecological fallacy- an error in reasoning in which incorrect conclusions about individual-level processes are drawn from group-level dataCausation and Experimental Design - Chapter 6- criteria of causation- deterministic vs. probabilistic- necessary and sufficient- necessary: Y will not occur without X- sufficient: X will


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