Agency Records, Content Analysis, and Secondary Data

Chapter 10

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Introduction

Data from agency records: agencies collect a vast amount of crime and CJ data

Secondary analysis – analyzing data previously collected

Content analysis – researchers examine a class of social artifacts (typically written documents)

Topics Appropriate for Agency Records

Most commonly used in descriptive or exploratory research

Agency records can also be used for explanatory studies

Applied studies

Content analysis often center on links between communication, perceptions of crime problems, individual behavior, CJ policy

Types of Agency Records

Published Statistics – government organizations routinely collect and publish compilations of data (e.g., NCVS, Census Bureau, BJS; often available in libraries and online

Nonpublic Agency Records – agencies produce data not routinely released (e.g., police departments, courthouses, correctional facilities)

New Data Collected by Agency Staff – collected for specific research purposes

Less costly

Allows the researcher more control

Example: Agency Data

  • The Pennsylvania Sentencing Commission makes their sentencing data available to researchers. The data is accessible through their website (http://pcs.la.psu.edu/data) and costs $70.00 per year requested. Using this data, researchers have published several articles and have generated a great deal of knowledge regarding sentencing decisions and the factors that affect those decisions.

Reliability and Validity Problems

  • Social production of data: most criminal justice record keeping is a social process

Most data reflects reactions to behaviors

  • Agency data are not designed for research

Data reflect internal agency needs that might not be the same as research needs

  • Tracking people, not patterns
  • Error increases as volume of data increases

Content Analysis

Content analysis: systematic study of messages; can be applied to virtually any form of communication

Decide on operational definitions of key variables

Decide what to watch, read, listen to & time frame

Analyze collected data

Well-suited to answer “Who says what, to whom, why, how, and with what effect?”

Aspects of Sampling and Coding in Content Analysis 1

First establish your universe, then your units of analysis and sampling frame, then sample

Communications need to be coded according to some conceptual framework

Choice between depth & specificity of understanding:

Manifest content – visible, surface content – similar to using closed-ended survey questions

Latent content – underlying meaning

Aspects of Sampling and Coding in Content Analysis 2

Reminders:

Remember operational definition of variables, and their mutually exclusive & exhaustive attributes

Pretest coding scheme

Assess coding reliability via intercoder reliability method and test-retest method

Illustrations of Content Analysis: Violence in Video Games

  • Thompson & Haninger (2001) sampled 55 of over 600 E-rated games
  • Experienced undergrad gamer played for 90 minutes or until game reached natural conclusion
  • Experienced gamer/researcher and undergrad gamer reviewed videotape of video gaming session
  • Coded: # of violent incidents, # of deaths, drugs/alcohol/tobacco, profanity and sexual behavior, weapon use, explicit music
  • Measured duration of violent acts and # of deaths to length of game playing for standardized measures

Illustrations of Content Analysis: Gang-Related Homicides

  • Analyzed police case files over a 10-year period in St. Louis
  • First classified case as gang-related or not
  • Then distinguished between gang-motivated and gang-affiliated homicides (after conceptualizing both)
  • Interrater reliability was extremely important

Secondary Analysis

  • Sources

Interuniversity Consortium for Political and Social Research (ICPSR): central repository of data collected by social science researchers

National Archive of Criminal Justice Data (NACJD): source of criminal justice data established by BJS

  • Advantages – cheaper, faster, benefit from work of skilled researchers
  • Disadvantages – data may not be appropriate to your research question; least useful for evaluation studies

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