Many times, questions that researchers ask can be answered by data that has already been collected for some other purpose. Existing data, also known as secondary data and archival data, is data collected for a purpose unrelated to the current study. Criminal justice scholars have a wealth of data that has already been collected by other researchers as well as from the daily workings of the components of the criminal justice system. Several government and nongovernment organizations have instituted many programs to make criminal justice data available to the research community. For example, the National Institute of Justice (NIJ) has created the Data Resources Program to preserve data produced by NIJ-funded studies and to make them available for secondary analysis by other researchers. The NIJ describes the program this way:
When an NIJ-funded study ends, researchers submit their data to the National Archive of Criminal Justice Data, which has been collecting data since 1978. The National Archive was created as part of the Inter-University Consortium for Political and Social Research (ICPSR) at the University of Michigan. ICPSR provides access to the world’s largest archive of computer-readable social science data and offers training in both basic and advanced methods of quantitative analysis in social science research (NIJ, 2011).
Researchers can use data collected and disseminated by organizations such as the one discussed above, or they can obtain data directly from a source that collects it for another (often administrative) purpose. The use of archival data in criminal justice and criminology research is only overshadowed by survey research. According to a review of the criminal justice literature conducted by Kleck, Tark, and Bellows (2006), “Archival data, mostly drawn from criminal justice records, was used in 32 percent of the research; and official statistics were used in 26 percent of the studies.” They further concluded that “Secondary analysis of existing datasets was central to criminological research (58 percent of the studies).”
A major reason for the popularity of archival data is that it is much easier to collect and much, much cheaper to obtain (often at no cost). Much of the “grunt work” of cleaning and organizing the data may already have been done by experts, making the data easier to use. Even when raw data is gathered from a primary source, it still may be in an electronic form such as a spreadsheet, eliminating the time-consuming process of data entry. Even when archival data cannot answer specific research questions, it may still prove useful. For example, information about the demographic characteristics of a particular city or county may be available from the Census Bureau.
When searching for possible archival data sources, the first step is to consider the scope of your research question. If the question is national in scope, then there may be federally funded datasets that can answer your questions, as well as federally collected statistical information. In an era of government accountability, much is measured and recorded. Nearly every federal agency will have quantified information about its activities. Many federal agencies also collect information on state and local conditions. The FBI’s Uniform Crime Reports program is a good example of this. The program collects data from nearly every law enforcement agency in the United States. With sufficient diligent searching, data for every state and many localities can be located.
Another potential use of archival data is to conduct longitudinal studies. If the necessary information is available, a new wave of data gathering can be compared to the archival data to track changes over time. Thus, the existence of archival data may eliminate the biggest barrier to longitudinal research—the inordinate amount of time that such studies inherently take. In other words, new data can be collected and merged with old data to create a longitudinal data set.
Also of interest to those conducting research with archival data is the idea of eliminating threats to validity. When multiple data sets converge in the same place, many threats to validity (e.g., experimenter bias) can be ruled out. The same statistical conclusions based on different data sets offer strong support for the contention that experimental effects are in operation, and chance was not the explanation. Often, archival data comes from national, grant-funded studies. This equates to large sample sizes, which equates to high levels of statistical power that researchers could never reproduce on a small scale. This point is especially salient to the student researcher, whether doing a project for a research methods class or writing a dissertation.
Many social scientists steeped in the methods of quantitative research may never consider potentially valuable sources of information that have been stored in the form of documents and archives. This is because some information is qualitative in nature and does not lend itself to statistical analysis. When a researcher is interested in essentially qualitative questions such as agency policies, the documents and archives can be extremely valuable sources of information.
Documents produced by agencies and organizations can provide the researcher with a wealth of qualitative information. For example, a police department’s policy documents concerning racial profiling can provide insight into whether public claims of “doing things differently” are being met in any substantial way. In other words, documents produced within an agency can confirm or refute information gleaned from other methods.
Physical artifacts are also of potential use to the researcher. These methods are commonly associated with archeology but are of use to other social science researchers as well. For example, a researcher interested in the “militarization of police” may inventory police equipment to determine what proportion is of a military character. A researcher interested in the use of technology by the police may search for the presence of digital devices in offices, on officers’ person, and in patrol cars.
Modification History File Created: 07/25/2018 Last Modified: 07/25/2018
This work is licensed under an Open Educational Resource-Quality Master Source (OER-QMS) License.