criminal justice

A variety of methods and designs can be used in criminal justice research. Both qualitative and quantitative methods are valid approaches to the sociological questions researchers will have when faced with presenting problems and issues. Ideally, criminal justice research should remain relevant, grounded in theory, and applicable to public policy or practice. Criminal justice policies and procedures can and should be evidence-based. Scientific research helps to identify which interventions or policies work, and which do not, based on quantitative data or on phenomenological factors like public opinion.
The two main branches of social science research include qualitative and quantitative designs. Qualitative research is not necessarily inferior to quantitative research in the social sciences because measurable outcomes cannot account for all aspects of the human experience. Therefore, researchers will often use qualitative methods like in-depth interviews, case studies, and focus groups in order to gather information, ask open-ended questions, and ascertain variables that can later be tested more empirically. Qualitative research can therefore become the forerunner to quantitative research. Many criminal justice researchers also opt for mixed methods or multimethod approaches, which allow for the integration of data from both types of studies (Maxwell, Chmiel & Rogers, 2016). Unlike quantitative research, qualitative research is driven by questions and not hypotheses, and does not purport to establish causal or even correlative connections between variables. Quantitative research is based on the scientific method.
Components of criminal justice research that are shared in common among both qualitative and quantitative research methods include the necessity of defining terms (operationalizing), outlining the gaps in the literature or motivation for the current research, and explaining the researcher’s theoretical orientation. Research often follows from theory, but research can also inform or enhance existing criminal justice theory. Likewise, researchers need to explain why they selected the type of design and methodology used in the study whether it is qualitative and quantitative research. Issues related to reliability and validity are as important in qualitative as in quantitative research in the social sciences.
Quantitative research follows the five steps of the scientific method, regardless of research design. The five steps of the scientific method include the making of observations, the formulation of research questions, the distillation of questions into testable hypotheses (prediction), carrying out the actual test (experimentation), and then communicating the results to a community of one’s peers in order to stimulate further inquiry or to replicate results (Flom, 2018). Taken together, these five steps form the backbone of any scientific research, including research that addresses topics pertinent to criminology and criminal justice. However, there are many different kinds of quantitative research designs that can be used. The criminal justice researcher selects a specific type of research design not on a whim or personal preference, but based on the nature of the research questions and hypotheses. Some hypotheses lend themselves to experimental designs, but not all research questions can be tested using experimental methods.
Criminal justice researchers use numerous types of experimental research designs including true experiments that are the gold standard in the social sciences. True experiments involve both random population selection and random assignment, and ideally large enough sample sizes. An experimental research design establishes causality between the independent and dependent variable by controlling strictly for any extraneous variables that could impact the reliability or validity of the study (“Quantitative Approaches,” n.d.). For example, a criminal justice researcher might study the effect of a drug treatment program on reducing recidivism rates in the community. The independent variable is the condition of either taking or not taking the drug treatment program, and the dependent variable would be recidivism, measured using specific instruments. With experimental and other quantitative research, the researchers need to carefully clarify the tools and instruments they are using, clarify why those tools or measures are accurate and relevant, and then report results both in terms of raw data and statistical analyses.
When true experimental methods are not possible, researchers in criminal justice have other options. One option is a quasi-experimental design. A quasi-experimental design may be warranted if the researcher cannot adequately manipulate the independent variable, which is common in real world criminal justice settings. Also, a quasi-experimental research design is indicated when the researchers cannot perform random assignment. Quasi-experimental designs can still be used to determine cause and effect using statistical analysis of data. For example, the researcher wants to investigate the impact of a drug treatment program on recidivism rates but the researcher also has no control over which members of the inmate population enrolled in that program. In a situation like this, the researcher would still be able to take the raw data from participants who had been enrolled in the drug treatment program and those that were not enrolled. Although random assignment and independent variable manipulation was not possible, it is still possible to control for extraneous variables like race, class, gender, and type of crime committed, as well as establish causality between program participation and recidivism rates, when using a quasi-experimental design.
Sometimes, criminal justice researchers need to use correlational designs. Correlational research designs still rely on the scientific method, as with true experiments and quasi-experiments. However, with a correlational design the researchers cannot determine causality or directionality between the two variables. The results of the study must be carefully presented and interpreted so as not be misleading. Statistical analyses are still used, but the implications of the study are different from what they would be if causality had been assessed. For example, a researcher wanting to measure the correlation between participation in a drug treatment program and recidivism rates might conduct a nationwide study that simply surveyed participants, and then correlated those results with recidivism rates in those respective jurisdictions. The researchers would not have been able to tell if any other factors, such as geography, age, or demographic features had any bearing on recidivism rates or even if legislation or policy initiatives were involved. Yet the researchers can at least show that there is a relationship between participation in drug treatment programs and recidivism. Even if the researchers found that participation in drug treatment programs increased recidivism, they would still have found a potentially meaningful correlation from the data set.
Descriptive research is the least scientifically robust of all the quantitative methods used in criminal justice. However, descriptive research provides a beginning to critical inquiry into a known or suspected phenomenon. Researchers use descriptive methods to gather observational data such as crime rates, victim characteristics, or demographic data. Whether using descriptive, correlational, quasi-experimental, or experimental designs, the researchers can use many different methods of data collection, sampling, and data analysis. Methods include the use of metrics or measurement systems, personality or psychological assessments, surveys, or existing data sets like the National Crime Victimization Survey (NCVS) (“Criminology and Criminal Justice Research: Methods - Quantitative Research Methods,” n.d.). All types of assessments, instruments, and tools used to gather data need to be valid in order to yield credible results. Construct validity refers to whether the instrument measures what it intends to measure, while content validity refers to how well or accurately it actually measures that criterion.
Most qualitative and quantitative research designs can be longitudinal in nature. Longitudinal studies involve testing the same sample over a long period of time. In quantitative research, longitudinal designs involve seeing how an intervention impacts the same population over time. Longitudinal designs are especially helpful in criminal justice research because human beings and societies can change dramatically over longer periods of time, but change little in the short run. If a researcher wants to examine the efficacy of a specific drug treatment modality on a specific subset of the population, a longitudinal design would be in order. The researcher could select a specific population such as women of color, and a specific treatment intervention. Then, the researcher would be able to see whether the sample population experienced any hypothesized changes over five or ten years.
Whether using qualitative methods, quantitative methods, or mixed methods, criminal justice researchers also need to use credible techniques for sampling their population. Random sampling is ideal because it increases the reliability of the results; a sample that is taken only from one community cannot be considered as representative of the entire population as a sample that is taken from many different communities over diverse and broad geographic zones. While large sample sizes are not possible with qualitative research, they are in quantitative research. Large sample sizes improve the reliability of the results because the standard deviation and other statistical measures will be more accurate. Reliability and validity are the most important concerns for criminal justice researchers, no matter what their field of interest or research questions.








References

“Criminology and Criminal Justice Research: Methods - Quantitative Research Methods,” (n.d.). http://law.jrank.org/pages/923/Criminology-Criminal-Justice-Research-Methods-Quantitative-research-methods.html
Flom, P. (2018). Five characteristics of the scientific methods. Sciencing. https://sciencing.com/five-characteristics-scientific-method-10010518.html
Maxwell, J.A., Chmiel, M. & Rogers, S.E. (2016). Designing integration in multimethod and mixed method research. In Hesse-Biber, S.N. & Johnson, B. (Eds.) The Oxford Handbook of Multimethod and Mixed Methods Research Inquiry. Oxford: Oxford University Press.
“Quantitative Approaches,” (n.d.). Center for innovation in research and teaching. https://cirt.gcu.edu/research/developmentresources/research_ready/quantresearch/approaches