What you'll learn in this course
Not everything that is faced can be changed, but nothing can be changed until it is faced. - James Baldwin
Racism is Systemic
It's not hard to find inequities in data. All you really have to do is open your eyes.
As an analyst I've spent a career with my head in datasets of all sorts. I have been a part of large research and evaluation studies in health, urban development, criminal justice, and education. It doesn't matter the area of study, when opening a data set that includes data on race and ethnicity, chances are strong that I will see our inequity reflected in the numbers.
As a designer, cartoonist, and blogger, I also know how hard it is to help people see what they would not like to see (self included). The uncomfortable facts that put into question our role in perpetuating a culture of white supremacy and racial inequality.
This is a course about making the numbers real.
There is no need to cherry pick. You don't need to be super selective to find numbers to share. Numbers that could be used to support anti-racist causes are everywhere, hidden in plain sight and in public data sources.
But if you want the numbers to have an impact, you have to make them real. You have to make them hard to ignore.
That is the point of this course.
We'll start with a module on a process I call localizing data.
The concept is simple, one way to make the data real is to show that the trends persist in your backyard. Data shared at federal, and event state, levels are too easy "to other". To pretend that they don't apply to your community.
But if you can show that the trends persist even when localized, it makes the numbers harder to ignore.
It also makes it easier to take action. As you can embed the data into your emails to politicians and police chiefs, strengthening your case.
If this course is useful, I'll make additional modules focused on some other strategies.
I am launching this course for free. And then keep it free.
If you enjoy the course, and want to show appreciation, pay it forward.