Criminal Justice Research Methodologies Quiz

Research in Criminal Justice

• The distinction between basic and applied research in criminal justice is sometimes blurred, but most research relevant to criminal justice practitioners falls more towards the applied end of the research continuum.
• Competent research can enhance the quality of day-to-day decisions and help administrators manage human and financial resources efficiently.
• Good research can significantly improve the formulation and implementation of policies and programs in the criminal justice system.
• There is a distinction between quantitative, qualitative, and mixed methods research approaches in social science research.
• Contemporary researchers have identified false and misleading distinctions and recognized the degree to which good research often involves elements of both quantitative and qualitative approaches.
• The quantitative approach in research is rooted in positivism and seeks general and universal truths through objective inquiry, emphasizing numerical measurement of variables and statistical analysis.
• Data in quantitative studies are gathered either directly in numerical form or in other kinds of measurements that can be readily converted to numbers.
• Data analysis in a quantitative methodology relies heavily on statistical procedures, and research reports include tables, graphs, equations, and statistical probabilities.
• Quantitative researchers tend to ally themselves more with the natural sciences.
• Emile Durkheim was a pioneer in quantitative social analysis, studying the relationship between suicide rates and various statistical indicators of social disorganization in European countries in the 19th century.
• Mixed methods research (MMR) integrates or mixes qualitative or quantitative approaches within a single investigation, study, or program of inquiry, enabling a more complete utilization of data than separate approaches.
• The debate between quantitative and qualitative methodologies has mainly subsided in recent years, and researchers now integrate or mix elements of both approaches within a single investigation.

Mixed-Methods Research in Social Science

• Qualitative researchers use participant observation and interviews for formulating research issues and variables, a strategy that has become more sensitive to sampling problems.
• Qualitative researchers have increasingly turned to questionnaires and structured interviews to supplement information obtained through participant observation.
• Both quantitative and qualitative researchers use questionnaires and interviews to acquire information about respondents' feelings, ideas, beliefs, and values.
• Attention must be given to the criteria of causal inference in explaining human conduct, regardless of the research style chosen.
• Due to the growing use of questionnaires and quantifiable data, qualitative researchers have become less suspicious of basic statistics data analysis.
• Research results should be accessible to the well-educated layperson, a standard set by qualitative researchers but increasingly recognized by quantitative researchers.
• The differences between quantitative and qualitative research are not as great as portrayed, and good researchers appreciate the advantages of both approaches.
• Mixed-Methods Research (MMR) involves combining at least one qualitative and one quantitative research component in a single investigation, study, or program of inquiry.
• MMR aims to strengthen study conclusions, improve knowledge, and add validity to the study through triangulation, complementarity, and other purposes.
• In most MMR studies, there are three sets of hypotheses: quantitative, qualitative, and integrated from both methodologies.
• MMR can be achieved through six basic design approaches, depending on the grounding in theory, priority of the quantitative or qualitative strategy, sequence of data collection, and point of integration of data.
• Sequential explanatory methods, one of the six basic design approaches, involves collecting quantitative data first and integrating it with qualitative data during interpretation to further explain the quantitative results.

Mixed Methods Research (MMR) Designs and Evaluation Research

• MMR designs include sequential informative, concurrent triangulation, concurrent nested, and concurrent transformative approaches.
• Sequential informative design allows for the collection of quantitative and qualitative data in any order, integrated during interpretation.
• Concurrent triangulation design involves collecting and integrating quantitative and qualitative data simultaneously during interpretation.
• Concurrent nested design embeds quantitative and qualitative data collection processes within each other and integrates data during analysis.
• Concurrent nested design is useful for gaining broader perspectives and studying separate groups or various levels in an organization.
• Concurrent transformative approach heavily relies on theory and allows for investigation of phenomena on distinct levels, integrating data during analysis or interpretation.
• MMR strengths include in-depth investigation and providing a more meaningful understanding of a phenomenon.
• MMR allows for a rigorous system of supporting findings of quantitative and qualitative data in research.
• MMR challenges include time-intensive data analysis, potential bias, and the need for expertise in integrating data.
• MMR study designs may require more than one researcher involvement and careful planning and execution.
• Evaluation research, also known as program evaluation, assesses the extent to which a program achieves intended goals and its cost-effectiveness.
• Evaluation research provides scientific information to guide public policy by offering measurable feedback on programs and activities.

Predictive Research and In-House, Hired-Hand, and Third-Party Research

• Minority citizens complain about police practices leading to African Americans driving expensive cars in wealthy neighborhoods being pulled over without direct evidence of an offense.
• Law enforcement interventions should be governed by criteria like "probable cause" beyond statistical associations generated by predictive research.
• The predictive criteria are too simple, leading to numerous false positives and taking place in a political context often overlooked by researchers.
• Prediction research has potential benefits, but significant problems need to be overcome before it can be fully realized.
• Progress has been made in understanding contributors to delinquency and crime, but accurate predictions are hindered by the involvement of many variables and weak associations with desirable outcomes.
• Simple predictive instruments prone to substantial prediction errors, while complex rating instruments are difficult to apply to individual cases.
• Validation and refinement of predictive scales, especially with different populations, are essential to reduce prediction errors.
• Scientifically based prediction can be as good as or better than other forecasts, but its use should be justified based on the risks and potential costs of false positives or negatives.
• Research projects can be categorized as in-house, hired-hand, or third-party research based on the relationship between the researchers and those being researched.
• In-house research is conducted by the staff of the organization being studied, focusing on activities or aspects of the organization.
• Hired-hand research is carried out by an independent outside organization paid by the organization under study.
• Third-party research is conducted by an independent outsider with greater independence and freedom in the research project.