Efficiency in Processing Sexual Assault Kits in Crime Laboratories and Law Enforcement Agencies, United States, 2013-2014 (ICPSR 36747)

Version Date: Nov 29, 2018 View help for published

Principal Investigator(s): View help for Principal Investigator(s)
Kevin Strom, RTI International

https://doi.org/10.3886/ICPSR36747.v1

Version V1

These data are part of NACJD's Fast Track Release and are distributed as they there received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except of the removal of direct identifiers. Users should refer to the accompany readme file for a brief description of the files available with this collections and consult the investigator(s) if further information is needed.

This study presents a research-informed approach to identify the most efficient practices for addressing un-submitted sexual assault kits (SAKs) that accrue in U.S. law enforcement agencies (LEAs) as well as untested SAKs pending analysis in crime laboratories. The study examined intra- and interagency dynamics associated with SAK processing efficiency in a linked sample of crime laboratories. SAK outputs and inputs were assessed for laboratories that conduct biological forensic analysis and LEAs that submit SAK evidence to these laboratories. Production functions were estimated to examine effects of labor and capital inputs, in addition to policies, management systems, and cross-agency coordination on efficiency. Six jurisdictions were recruited for site visits, and qualitative methods were used to understand how LEAs, laboratories, and prosecutors implement practices that affect efficiency.

This study contains 7 data files including:

  1. Crime Lab_Raw.dta (n=147; variables =242)
  2. Crosswalk File.dta (n=2337; variables=2)
  3. lab_analysis_sample_2017-04-06.dta (n=132; variables=92)
  4. LEA Communication LCAs.dta (n=321; variables=15
  5. merged_analysis_file_JH2017-04-30.dta (n=273; variables=117)
  6. policy Class probabilities_LABS.dta (n=139; variables=19)
  7. SAK LAB COMMUNICATION LCA.dta (n=134; variables=15)

Strom, Kevin. Efficiency in Processing Sexual Assault Kits in Crime Laboratories and Law Enforcement Agencies, United States, 2013-2014 . Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2018-11-29. https://doi.org/10.3886/ICPSR36747.v1

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United States Department of Justice. Office of Justice Programs. National Institute of Justice (2013-NE-BX-0006)

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Access to these data is restricted. Users interested in obtaining these data must complete a Restricted Data Use Agreement, specify the reasons for the request, and obtain IRB approval or notice of exemption for their research.

Inter-university Consortium for Political and Social Research
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2013 -- 2014
2013 -- 2014
  1. These data are part of NACJD's Fast Track Release and are distributed as they there received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except of the removal of direct identifiers. Users should refer to the accompany readme file for a brief description of the files available with this collections and consult the investigator(s) if further information is needed.

  2. Please note that the qualitative data from Law Enforcement Agency site visits are not available under NACJD's Fast Track Release.

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The purpose of this study is to provide a research-informed approach to identify the most efficient practices for addressing the submission of Sexual Assault Kits in U.S. Law Enforcement Agencies and the testing of Sexual Assault Kits in laboratories.

Data was collected in three different phases. In Phase I, a national survey was administered to state, county, and municipal laboratories that conduct biological forensic analysis, and an additional survey was given to a sample of law enforcement agencies (LEAs) that submit sexual assault kits (SAK) evidence to these laboratories. Questions were designed to assess SAK outputs (e.g., submission/testing rates) and inputs (e.g., labor, capital, policies, interagency communication). In Phase II, production functions were estimated to examine effects of labor and capital inputs, in addition to policies, management systems, and cross-agency coordination on efficiency. Lastly, in Phase III, six jurisdictions were recruited for site visits, and qualitative methods were used to understand how law enforcement agencies (LEAs), laboratories, and prosecutors implement practices that affect efficiency.

The sampling plan began with a national survey of state and local crime laboratories that conduct biological forensic analyses (n = 222). Laboratories were drawn from the Bureau of Justice Statistics' 2009 Census of Publicly Funded Forensic Crime Laboratories (CPFFCL). The final response rate was 67% (147 laboratories). The second step was to select a sample of law enforcement agencies (LEAs) from the population of LEAs submitting forensic evidence to these responding laboratories, with the goal of sampling four LEAs per laboratory (n = 588). The population of LEAs (from the Uniform Crime Reports database) was matched with the sample of jurisdictions reported by the laboratory agency, and a merged list was created with both the sampled laboratories and the population of LEAs submitting to those laboratories. The merged list was used as the LEA sampling frame from which lead letters and reminders were developed and sent to each agency's chief. A total of 321 LEAs responded to the survey.

Cross-sectional

law enforcement agencies, crime laboratories, linked law enforcement and laboratory pairs

Law Enforcement Agencies, Crime Laboratories

Crime Lab_Raw.dta (n=147; variables= 242)- This file's variables refer to how sexual assault kits are handled in crime labs. This includes: policies and procedures, number of sexual assault kit (SAK) requests, number of SAKs processed, funding, communication between law enforcement and crime labs, etc.

Crosswalk File.dta (n=2337; variables=2)- This file only contains 2 variables that are ID numbers for crime labs and law enforcement agencies.

lab_analysis_sample_2017-04-06.dta (n=132; variables=92)- The variables in this file are closely related to the variables in file 'Crime Lab_Raw.dta' listed above.

LEA Communication LCAs.dta (n=321; variables=15)- This file contains variables relating to the communication between law enforcement agencies and labs, agencies, victims, suspects, etc.

merged_analysis_file_JH2017-04-30.dta (n=273; variables=117)- This file contains variables similar to those mentioned above. Some examples of these variables are: number of SAKS collected, number of SAKS submitted, How are SAKs collected, evidence retention for guilty and non-guilty defendants, average number of SAKs analyzed per analyst.

policy Class probabilities_LABS.dta (n=139; variables=19)- This file contains variables that explore the status of cases whether it be acceptance or removal etc.

SAK LAB COMMUNICATION LCA.dta (n=134; variables=15)- This file contains variables regarding what case info labs receive.

67 percent of (survey of crime laboratories)

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Notes

  • These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

  • The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.

  • One or more files in this data collection have special restrictions. Restricted data files are not available for direct download from the website; click on the Restricted Data button to learn more.

  • The citation of this study may have changed due to the new version control system that has been implemented.