NCJ Number
243912
Date Published
January 2013
Length
8 pages
Annotation
In order to facilitate productive partnerships between criminal justice practitioners and academic researchers in the criminal justice field, this study developed recommendations for both practitioners and researchers; this paper offers recommendations for researchers.
Abstract
First, practitioners and researchers who participated in this study nearly unanimously agreed that a strong relationship based on trust is the most critical component of a successful collaboration. Second, researchers should network with criminal justice practitioners, professional organizations, and colleagues in the community. Third, clearly communicating expectations and mutually agreeing on project goals are necessary for a successful collaboration. Fourth, researchers should initiate and value practitioners' involvement in their research, given their direct experience with individuals, programs, and policies in the criminal justice system. Fifth, researchers as well as the researcher-practitioner relationship will benefit from the researcher being a participant-observer in the practitioner's responsibilities and decisionmaking. Sixth, researchers can enhance the working relationship with practitioners by acquainting them with the research processes of design, data collection, data analysis, and drawing implications of research findings for policy and practice. Seventh, researchers should maximize the usefulness of products for practitioners. Eighth, since collaboration involves more input and involvement from practitioners, researchers should budget for extra time in conducting the research. These recommendations stem from individual interviews and focus groups, data analysis, and a Web-based survey.
Date Published: January 1, 2013
Downloads
Similar Publications
- Evaluation of Cannabis Product Mislabeling: The Development of a Unified Cannabinoid LC-MS/MS Method to Analyze E-liquids and Edible Products
- THEORETICAL PERSPECTIVES ON ALIENATION IN THE PRISON SOCIETY - AN EMPIRICAL TEST
- A Multivariate Heavy-tailed Integer-valued GARCH Process with EM Algorithm-based Inference