This document is a template to be used to work our racial equity tools.
Results Based Accountability
For more on this, read the GARE resource:
Currently across the country, regardless of region, racial inequities exist across every indicator for success—including health, criminal justice, education, jobs, housing, and beyond. We know these inequities are incongruent with our aspirations. The Government Alliance on Race and Equity (GARE), a joint project of the Haas Institute for a Fair and Inclusive Society at the University of California, Berkeley and Center for Social Inclusion, recognizes that we can and must do better. We know that government has a key role in advancing racial equity, and therefore are modeling at the local level how it is truly possible for government to advance racial equity and to develop into an inclusive and effective democracy.
We know change is possible with intentionality and focus. We must recognize that from the inception of our country, government at the local, regional, state, and federal level has played a role in creating
and maintaining racial inequities. Though we’ve made many strides toward racial equity, policies and practices have created and still create disparate results—even if the intention to discriminate is not present. Despite progress in addressing explicit discrimination, racial inequities continue to be deep, pervasive, and persistent across the country. We are at a critical juncture with an exciting new role for government—to proactively work for racial equity.
Our goal goes beyond closing the gaps; we must improve overall outcomes by focusing efforts on those who are faring the worst. Deeply racialized systems are costly for us collectively and depress outcomes and life chances for communities of color. To advance racial equity, government must focus not only on individual programs, but also on policy and institutional strategies that create and maintain inequities. GARE uses a six-part strategic approach geared to address all levels of institutional change.
Using data from the indicators we just talked about, what root causes get in the way of our desired results?
When working to develop outcome and desired result statements be sure to always try to elevate the statement to the highest level you can so that it intersects with as much as possible when using the “community lens.”
Using root causes that seem most vital to remove, what Actions (experiments) can should we try?
A simple board to see what flushed out actions/ideas are to be ranked and/or in progress.
What actions did we agree to do?
Which ones did we actually do?
What did we expect to happen?
Based on what we learned, what are we going to do next?
I've listed some material for those who are interested in learning more about PopcornFlow
Here are the database tables that power the doc. You can use this page to explore how I've put them together, and to clear the databases.
If you don't so much like the guided method, I've also created a page that shows a full end-to-end PopcornFlow board, adapted for this doc.
My notes in putting this doc together, along with some thoughts I have around PopcornFlow.
and create experiments for them