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Discovering Nonprofit Impact Using a Racial Equity Lens – Part III: Action-Oriented, Results-Based, and Data-Driven Logic Model

November 19, 2:00 pm EST - 3:30 pm EST

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Discovering Nonprofit Impact Using a Racial Equity Lens Part III connects topics discussed in Part II on the theory of change to the logic model. This webinar will provide an overview of the steps to develop an action-oriented, results-based, data driven logic model. Action-oriented logic models give a high level picture of actions the nonprofit will take to impact racial disparities.

Data-driven logic models include information on what type of data will be collected from activities and how often, while keeping a racial equity lens focus on data collection. Results-based logic models ensure that every item on the logic model is connected to an intended result. This connection helps to make it easier for nonprofits to “tell the story behind the data.” It also helps to ensure that all nonprofit activities and efforts remain laser focused on impacting racial wealth disparities.

INstructor

  • Quisha Brown, Nonprofit Consultant

You will learn:

  • How the relationship between the theory of change and the logic model is accomplished
  • How KPI’s connect to the outcomes within the logic model
  • The differences between outputs and outcomes in a logic model
  • How activities are defined in a logic model so that the intended outcomes are measurable
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Details

Date:
November 19
Time:
2:00 pm EST - 3:30 pm EST
Event Category:
Event Tags:
Website:
https://training.ncrc.org/eweb/DynamicPage.aspx?Site=NCRC&WebCode=EventDetail&evt_key=0b7f12e0-83e8-4f4a-9697-0860e4d55897

Redlining and Neighborhood Health

Before the pandemic devastated minority communities, banks and government officials starved them of capital.

Lower-income and minority neighborhoods that were intentionally cut off from lending and investment decades ago today suffer not only from reduced wealth and greater poverty, but from lower life expectancy and higher prevalence of chronic diseases that are risk factors for poor outcomes from COVID-19, a new study shows.

The new study, from the National Community Reinvestment Coalition (NCRC) with researchers from the University of Wisconsin–Milwaukee Joseph J. Zilber School of Public Health and the University of Richmond’s Digital Scholarship Lab, compared 1930’s maps of government-sanctioned lending discrimination zones with current census and public health data.

Table of Content

  • Executive Summary
  • Introduction
  • Redlining, the HOLC Maps and Segregation
  • Segregation, Public Health and COVID-19
  • Methods
  • Results
  • Discussion
  • Conclusion and Policy Recommendations
  • Citations
  • Appendix

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