Optimizing Video Surveillance in Correctional Settings, Minnesota, 2015-2019 (ICPSR 37984)

Version Date: Apr 11, 2024

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Principal Investigator(s):
Bryce Peterson, Urban Institute

https://doi.org/10.3886/ICPSR37984.v2

Version V2 ()

  • V2 [2024-04-11]
  • V1 [2022-03-30] unpublished
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Summary

The Urban Institute and the Minnesota Department of Corrections (MnDOC) attempted to improve the surveillance system in two state correctional facilities: Stillwater (STW) and Moose Lake (ML). The goal of this study was to conduct a rigorous process and impact evaluation of the steps that STW and ML took to optimize their surveillance systems, which included repositioning existing cameras, installing new cameras, and making other infrastructural upgrades. In addition, ML integrated an audio analytic technology in their system that would alert on-unit security staff through a visual and audio alert when it detected sounds associated with anger, fear, or verbal aggression.

The evaluation used a mixed-methods research design. Qualitative data collection included stakeholder interviews and in-depth observations of the camera operations at ML and STW before, during, and after the upgrades. The research team interviewed wardens, supervisors and officers working in the intervention units, and numerous other individuals who oversaw operations, investigations, information technology, and camera installation and configuration in ML and STW.

Quantitative administrative data were collected from ML and comparison facilities and comparative interrupted time-series (CITS) analyses were employed to examine changes in two outcomes (total misconduct incidents and guilty dispositions) following the intervention. To support the CITS, another unit in ML was identified that did not upgrade its surveillance system but was similar to the intervention housing unit in terms of population, architecture, and misconduct levels (internal comparison unit), and used the synthetic control method to create another comparison unit derived from the three other medium-security prisons operated by MnDOC (external comparison unit).

Citation

Peterson, Bryce. Optimizing Video Surveillance in Correctional Settings, Minnesota, 2015-2019. Inter-university Consortium for Political and Social Research [distributor], 2024-04-11. https://doi.org/10.3886/ICPSR37984.v2

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Funding

United States Department of Justice. Office of Justice Programs. National Institute of Justice (2015-R2-CX-K001)

Subject Terms

Geographic Coverage

Restrictions

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

Distributor(s)

Inter-university Consortium for Political and Social Research
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Time Period(s)

2015 -- 2019

Date of Collection

2015-01 -- 2019-12 (CITS data), 2019-07 (Site observations and interviews)
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Study Purpose

The purpose of this study was to:

  1. Identify technical and operational weaknesses/gaps in the surveillance systems of two Minnesota Department of Corrections (MnDOC) prisons: Stillwater (STW) and Moose Lake (ML);
  2. Develop an enhanced surveillance intervention to help MnDOC overcome some of these weaknesses/gaps;
  3. Implement the enhanced surveillance intervention, documenting the challenges and successes the project team encountered during the process; and
  4. Evaluate the impact of the enhanced surveillance intervention on correctional misconduct and perceptions of safety within the prisons.

Study Design

The Urban Institute and Minnesota Department of Corrections (MnDOC) developed site-specific implementation plans that detailed recommendations for improving and optimizing the surveillance systems in Stillwater (STW) and Moose Lake (ML) correctional facilities. Recommendations included the installation of new high-definition Internet Protocol (IP) cameras, infrastructural upgrades, and the integration of audio analytic technology in ML.

The research team worked closely with the MnDOC to collect data associated with the surveillance system and upgrades. Qualitative data collection included stakeholder interviews and in-depth observations of the camera operations at ML and STW before, during, and after the upgrades. Data were hand-coded and analyzed to identify high-level themes around whether the intervention was implemented as planned, issues that arose during the implementation and ongoing calibration of the system upgrades, and staff perceptions of success, challenges, and lessons learned from the project. The research team also received logs from ML on the audio analytic alerts integrated into their surveillance system that were analyzed to better understand the volume and types of alerts staff received.

Due to a significant incident at the STW facility, the research team opted to drop STW from the analyses of institutional safety and officer investigations and instead focused on the ML facility. Improvements to the ML system were implemented in two phases. First, in September 2017, ML staff upgraded officer viewing stations and replaced the intervention unit's existing analog cameras with new IP cameras. The second phase occurred in May 2018 and involved upgrading servers and installing new cameras in strategic locations to reduce blind spots. Data on misconducts and dispositions were collected from ML and its comparison facilities, which included another unit in ML that did not upgrade its surveillance system but was similar to the intervention housing unit in terms of population and misconduct levels (internal comparison) and three other medium-security prisons operated by MnDOC (external comparison). Multiple intervention comparative interrupted time-series (CITS) analyses were employed to observe how the count of total misconduct incidents and incidents resulting in guilty dispositions changed in the ML intervention unit after both phases of camera upgrades were implemented.

Sample

Respondents were selected from two correctional facilities in the state of Minnesota. Video surveillance information was collected from three correctional facilities, also in the state of Minnesota.

Time Method

Time Series

Universe

Incarcerated adult residents of two Minnesota correctional facilities.

Unit(s) of Observation

Event/Process, Individual

Data Type(s)

Mode of Data Collection

Description of Variables

Variables in the MnDOC comparative interrupted time-series (CITS) Analysis dataset include information pertaining to infractions such as dates of occurrence, location, and type of infraction. Variables in the Inmate Survey dataset include respondent demographics (age, ethnicity, and race), convictions, infraction records, and opinions on safety and recommendations.

Response Rates

47 percent of all inmates at Stillwater and Moose Lake correctional facilities responded to the Minnesota Prison Safety Survey.

Presence of Common Scales

None

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Original Release Date

2022-03-30

Version History

2024-04-11 The collection now includes the study's qualitative data component (Dataset 3: Observation and Interview Notes). Dataset 2 (Inmate Survey Data) was updated to include a supplemental CSV file containing full, un-truncated responses for the variable B_MAKE_SAFE. The ICPSR Codebook for Dataset 1 (MnDOC CITS Analysis Data) was updated to correct ICPSR Processing Notes. Minor revisions were also made to the study's metadata.

2022-03-30 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.

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Weight

A synthetic control method was utilized to generate external comparison units based on a weighted composite of the housing units in MnDOC's two other medium security facilities.

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Notes

  • 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.