It is important to study research methods to determine which method would work best in a particular scenario. Below we will examine the top five research methods used by criminologists today: survey, longitudinal, meta analysis, quasi-experimental research, cross-sectional research methods, and the gold standard of research methods – randomized control trial (RCT) method. (trudi)

3.2.1 Survey Research Method

Survey research is a quantitative and qualitative method with two important characteristics. First, the variables of interest are measured using self-reports. In essence, survey researchers ask their participants (who are often called respondents) to report directly on their own thoughts, feelings, and behaviors. Second, considerable attention is paid to the issue of sampling. In particular, survey researchers have a strong preference for large random samples because they provide the most accurate estimates of what is true in the population. In fact, survey research may be the only approach in which random sampling is routinely used. Beyond these two characteristics, almost anything goes in survey research. Surveys can be long or short. They can be conducted in person, by telephone, through the mail, or over the Internet. They can be about voting intentions, consumer preferences, social attitudes, health, or anything else that it is possible to ask people about and receive meaningful answers. Although survey data are often analyzed using statistics, there are many questions that lend themselves to more qualitative analysis.

3.2.2 Meta Analysis Research Method

Meta-analysis is a research method that involves combining data from multiple studies to draw conclusions about a particular research question or topic. The goal of a meta-analysis is to identify consistent patterns or trends across studies, which can provide more reliable and precise estimates of the effects of an intervention or factor than any single study could provide on its own.

To conduct a meta-analysis, researchers typically begin by identifying a research question and a set of studies that have investigated that question. They then use statistical methods to combine the results of those studies, often weighting each study according to its sample size or other factors. By combining the results of multiple studies, meta-analysis can help to identify consistent findings across studies, as well as identify factors that may explain variability in results across studies.

One example of how a criminologist might employ meta-analysis is to examine the effectiveness of a particular intervention aimed at reducing crime, such as a community policing program. By conducting a meta-analysis of studies that have investigated the effectiveness of community policing, a criminologist could identify whether the intervention consistently leads to reductions in crime across different settings, populations, and study designs. They could also identify factors that may moderate the effectiveness of the intervention, such as the quality of implementation, the characteristics of the community, or the nature of the crime problem being addressed. Such findings could help policymakers and practitioners to make more informed decisions about how to allocate resources and implement crime reduction strategies. (chat gpt)

3.2.3 Quasi-Experimental Research Method

The prefix quasi means “resembling.” Thus quasi-experimental research is research that resembles experimental research but is not true experimental research. Although the independent variable is manipulated, participants are not randomly assigned to conditions or orders of conditions (Cook & Campbell, 1979). Because the independent variable is manipulated before the dependent variable is measured, quasi-experimental research eliminates the directionality problem. But because participants are not randomly assigned—making it likely that there are other differences between conditions—quasi-experimental research does not eliminate the problem of confounding variables. In terms of internal validity, therefore, quasi-experiments are generally somewhere between correlational studies and true experiments.

Quasi-experiments are most likely to be conducted in field settings in which random assignment is difficult or impossible. They are often conducted to evaluate the effectiveness of a treatment or program. A criminal justice example of a quasi-experimental research method is the evaluation of a new correctional program in a state prison system. Suppose that a new educational program is implemented in one prison, but not in another prison, due to resource constraints. The correctional system may want to evaluate the impact of the program on the outcomes of the participating prisoners, such as recidivism rates or successful reentry into society after release.

To evaluate the program’s impact, researchers could use a quasi-experimental design by comparing the outcomes of prisoners who participate in the program with those who do not. However, since participation in the program is not randomly assigned, the researchers must take steps to control for other factors that may influence the outcomes, such as prior criminal history or demographic characteristics.

One way to control for these factors is to use statistical techniques, such as regression analysis or propensity score matching, to create comparable groups of participants and non-participants. The researchers can then compare the outcomes of these two groups to evaluate the program’s impact, while accounting for potential confounding factors.

This type of quasi-experimental research design can help correctional systems and policymakers to make informed decisions about the effectiveness of new programs, without requiring the time and resources necessary for a randomized controlled trial. However, it is important to note that quasi-experimental designs may be more prone to bias than randomized controlled trials, and therefore, the findings should be interpreted with caution. (trudi / chat gpt)

3.2.4 Cross-Sectional Research Method

A cross-sectional research method is a research design that involves collecting data from a sample of individuals at a single point in time. A criminal justice example of a cross-sectional research method is a survey of public attitudes towards the police. In this study, a sample of individuals from a particular community or region would be selected and asked to complete a survey about their perceptions of the police, their confidence in the police, and their experiences with the police.

The survey would be administered at a single point in time, such as over the course of a week or a month. The data collected from the survey would provide a snapshot of public attitudes towards the police in the community during that period.

The findings from this cross-sectional research method could help law enforcement agencies to understand the perceptions of the public towards their work, identify areas of concern, and develop strategies to improve police-community relations. For example, if the survey reveals that a significant portion of the community does not trust the police, law enforcement agencies may consider implementing programs to improve transparency and accountability, or increase community engagement efforts.

However, it is important to note that cross-sectional research designs can only provide a snapshot of a particular point in time, and cannot provide information about how attitudes and perceptions may change over time. Longitudinal research designs that track changes in attitudes over time may be necessary to fully understand how attitudes towards the police may be influenced by events or interventions. (trudi / chat gpt)

3.2.5 Randomized Control Trial (RCT) Research Method

A Randomized Controlled Trial (RCT) is a research method that involves randomly assigning participants to different groups, typically an intervention group and a control group, to test the effectiveness of an intervention or treatment. The goal of an RCT is to minimize bias and establish a causal relationship between the intervention and the outcome being studied.

Advantages

• Good randomization will “wash out” any population bias
• Results can be analyzed with established statistical tools
• Populations of participating individuals are clearly identified

Disadvantages

• Expensive in terms of time and money
• Volunteer biases: the population that participates in the study may not be representative of the actual entire population

A criminal justice example of an RCT is the evaluation of a new education program for first-time offenders. In this study, a group of first-time offenders would be randomly assigned to either the intervention group or the control group. The intervention group would participate in free college courses and research opportunities for college credit as well as other types of support to address the underlying causes of their criminal behavior. The control group, on the other hand, would not receive the education program or support and would continue with the traditional criminal justice process.

After the intervention period, both groups would be assessed for outcomes such as recidivism rates or successful completion of probation. The researchers would then compare the outcomes of the two groups to evaluate the effectiveness of the diversion program.

A RCT in this criminal justice setting would provide strong evidence of the effectiveness of the diversion program, since the random assignment of participants to groups would help to control for other factors that may influence the outcomes. By establishing a causal relationship between the intervention and the outcomes, this RCT could help policymakers and practitioners to make informed decisions about the implementation and expansion of the diversion program to reduce recidivism and improve outcomes for first-time offenders. (trudi / chat gpt)

3.2.6 Impact on People’s Lives

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession. It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

Specifically in the field of criminal justice, research is critical because it provides a scientific and evidence-based approach to understanding and addressing the complex problems and issues that arise in the justice system. Through research, criminal justice professionals can gain a better understanding of the root causes of crime, the effectiveness of different intervention programs, and the impact of various policies and practices on public safety and community well-being.

In addition, research helps to identify and address biases and disparities in the criminal justice system. Through rigorous and objective research, criminal justice professionals can gain a better understanding of the factors that contribute to disparities in policing, sentencing, and other aspects of the justice system, and develop evidence-based solutions to address these issues. The Crime Prevention Science sections of each chapter in this textbook provide examples of such research and these sections are included in every chapter to demonstrate how important research is to the improvement of our criminal justice system.

Overall, research is critical in the field of criminal justice because it helps to promote evidence-based practices, improve outcomes, and ensure that the justice system operates fairly and equitably for all.

3.2.7 Statistics on “Other Groups”

Conducting research relies on gathering accurate and reliable data. When analyzing inequities within the Criminal Justice System, race and ethnicity are two of the variables gathered and considered in the research. However, how race and ethnicity are represented in the research can skew the data and cause challenges. For example, the U.S. Office of Management and Budget (OMB) disaggregates race into the following categories:

• American Indian or Alaska Native
• Asian
• Black or African American
• Native Hawaiian or Other Pacific Islander
• White

And ethnicity into the following categories:

• Hispanic or Latino
• Not Hispanic or Latino

Simply using these categories can, in and of itself, cause distention and misinformation in how one self-identifies, in that not everyone feels they fit into these groupings. Over the years, the OMB has conducted reviews of race and ethnicity categories and have made some changes, and yet many still do not feel they fit within these prescribed groups. For example, someone may identify with the ethnicity of Hispanic or Latino but may not identify with any of the prescribed race categories. Thus if they chose to leave the race category blank the data would be incomplete or if the race category was a required field, the person may feel compelled to just choose one of the options, even if they didn’t identify as it, thus providing inaccurate information.

Although researchers have the ability to expand these categories, if they so choose, this too can cause misinformation as some research may have more disaggregated data than others. Researchers are also not required to expand these categories, except in a few specific situations, like those in the state of New York in which in December 2021, Governor Kathy Hochul signed New York State Law S.6639-A/A.6896-A. The law requires state agencies, boards, departments, and commissions to include more disaggregated options for Asian races to include: Korean, Tibetan, and Pakistani as well as more disaggregated options for Native Hawaiian or Other Pacific Islander races to include: Samoan and Marshallese (Governor Hochul Signs Package of Legislation to Address Discrimination and Racial Injustice, 2021).

This has led to a number of researchers including “other” categories, allowing individuals to thus choose if they don’t feel they identify with one of the specific categories. Some researchers have also included the fill-in-the blank model in which respondents then check the “other” box and specify their self-identified race. These two options, although more inclusive to self-identification, can lead to additional data reporting issues, in which researchers are not able to aggregate the data due to too many variations in responses. This same concern can be applied in additional data collection categories as well, when the category options are limited and thus have the potential to exclude certain individuals.

3.2.8 Statistics on Native American and Latinx

According to a Bureau of Justice Statistics report in 1999, Native Americans were incarcerated at a rate that was 38% higher than the national average (Greenfield, 1999). More recent data suggest that in jails 9,700 American Indian/Alaskan Native people – or 401 per 100,000 population – were held in local jails across the country as of late June, 2018. That’s almost twice the jail incarceration rates of both white and Hispanic people (187 and 185 per 100,000, respectively) (Zen, 2018). In 19 states, they are more overrepresented in the prison population compared to any other race and ethnicity (Sakala, L., 2010). Between 2010 and 2015, the number of Native Americans incarcerated in federal prisons increased by 27% (Flanigan, 2015). In Alaska, data published by the 2010 US Census revealed that 38% of incarcerated people are American Indian or Alaskan Native despite the fact that they make up only 15% of the total population (Sakala, 2010). Native youth are highly impacted by the US prison system, despite accounting for 1% of the national youth population, 70% of youth taken into federal prison are Native American (Lakota People’s Law Project, 2015). Native American men are admitted to prison at four times the rate of white men, and Native American women are admitted at 6 times the rate of white women(Lakota People’s Law Project, 2015).

Latinos are incarcerated at a rate about 2 times higher than non-Latino whites and are considered one of the fastest-growing minority groups incarcerated (Kopf, Wagner, 2015).