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Development of a Model Approach to Arrest Data Analysis

Agency: National Institute of Corrections

Assistance Listings
  • 16.602 -- Corrections_Research and Evaluation and Policy Formulation

Archived opportunityLast Updated: May 13, 2026

View version history on Grants.gov

Utilizing information and data specific to LaCrosse, County WI, develop a “model approach" to data analysis to determine arrest trends and provide tracking measures for criminal justice stakeholder review. Additionally, a corresponding curriculum framework will be developed allowing for teaching and learning around data accessibility, accuracy and consistency for the purposes of informing and monitoring data driven practices. The development of this model and framework will allow other localities to develop the capacity to understand and improve their current arrest data collection and analysis practices.

Eligibility

Eligible applicants

Miscellaneous

  • Other

Additional information

NIC invites applications from nonprofit organizations (including faith-based, community, and tribal organizations), for-profit organizations (including tribal for-profit organizations), and institutions of higher education (including tribal institutions of higher education). Recipients, including for-profit organizations, must agree to waive any profit or fee for services.NIC welcomes applications that involve two or more entities; however, one eligible entity must be the applicant and the others must be proposed as sub-recipients. The applicant must be the entity with primary responsibility for administering the funding and managing the entire program.NIC may elect to make awards for applications submitted under this solicitation in future fiscal years, dependent on the merit of the applications and on the availability of appropriations.

Grantor contact information

Description

Cameron Coblentz Phone 202-514-0053

Email

Application or Form Questions

ccoblentz@bop.gov

Documents

File nameDescriptionLast updated
17CS12_-_Model_Approach_to_Arrest_Data_Analysis_v1framework_added.pdf
17CS12
Jul 31, 2017 02:42 PM UTC

Link to additional information

NIC Website

Archived: September 30, 2017

Application process

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Award

$60,000

Program Funding

1

Expected awards

$--

Award Minimum

$60,000

Award Maximum

Funding opportunity number:

17CS12

Cost sharing or matching requirement:

No

Funding instrument type:

Cooperative agreement

Opportunity Category:

Discretionary

Opportunity Category Explanation:

--

Category of Funding Activity:

Other

Category Explanation:

The National Institute of Corrections (NIC) is a center for learning, innovation and leadership that shapes and advances effective correctional practice and public policy. The deliverables from this cooperative agreement will contribute to the mission of NIC by promoting the ongoing development and advancement of correctional practices by developing a model approach to arrest data analysis for the purposes of informing and monitoring data driven practices. A core resource of the Evidence- Based Decision Making Initiative is “A Framework for Evidence-Based Decision Making in Local Criminal Justice Systems” outlines a set of principles for effectively implementing EBDM. Principle Four states: “The criminal justice system will continually learn and improve when professionals make decisions based on the collection, analysis, and use of data and information” . EBDM policy teams identified a need to have a better understanding of local arrest trends and developing an accurate source of arrest data to rely on for future policy and practice change. NIC recognizes that this need is not limited to EBDM sites as many jurisdictions have challenges related to accessing reliable data for the purposes of informing and monitoring data driven practices. Therefore, a deliverable will include developing a model approach on data accessibility, accuracy and consistency for the purposes of developing and/or improving data driven practices.

History

Version:

2

Posted date:

July 31, 2017

Archive date:

September 30, 2017

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