How are our decisions in our data work accidentally harming the people in them that we care about?
How can we identify all of the subjective choices that make up a data process?
How can we gain practical tools and techniques to make those choices in a way that aligns with our equity priorities instead of sabotaging them?
How can we actually begin to address the overwhelming number of decisions we have to make while increasing scientific rigor, generating convincing and reliable results, and getting it done on time and on budget?
Upcoming Dates:
Tuesday, October 8th & Wednesday, October 9th
12 – 3pm ET
Monday, December 9th & Tuesday, December 10th
12 – 3 pm ET
What is this course?
The Foundations of Data Equity is We All Count’s flagship course in which we teach you how to apply the Data Equity Framework, a seven-step approach to identifying, making, defending, and celebrating your data process decisions in a way that is congruent with your equity priorities.
The course is delivered over two live 3-hour sessions by Heather Krause with an introvert-friendly, trauma-informed, interact-as-much-as-you-want participation system.
By the end, you will leave with:
- a set of practical skills to start immediately improving the equity in your data work,
- an open line of communication with Heather Krause and the WAC team, an online platform to connect (and stay connected) with your course’s cohort and the larger invaluable network of other WAC alumni.
- a set of concrete, real-world resources to help you pursue the work after the course.
- access to a full recording of the course for review and zoom-fatigue insurance.
Key Info:
Price: $495 USD per seat.
Format: Live Zoom training with optional participation as well as materials, resources, and community hosted on a private online learning space.
Length: Two 3-hour sessions, total time 6 hours.
Prerequisites: The Data Equity Primer is a prerequisite for this course. This course is a prerequisite for the Advancing the Data Equity Framework course.
More questions?
If you’d like to attend a Foundations of Data Equity training at a custom date or arrange private training for your team, please contact us for current pricing, group discounts, and schedule availability.
We All Count is committed to access to data equity information for everyone and as such offers a select amount of free or financially-aided seats in each course. Click here to apply.
Who is this for?
This workshop is ideal for people who design, collect, analyze, visualize, and make decisions with data as well as those who don’t work directly with data but need to communicate with data teams.
Our courses are designed with the assumption of little to no prior technical expertise in data and statistics. Don’t know the difference between a confidence interval and a point estimate? No problem. (Do know the difference? Prepare to get your mind blown!)
Our courses are designed with the assumption of little to no prior equity, DEI, social justice, or ethics training. Don’t know the difference between intersectional and multi-racial? No problem. (Do know the difference? Prepare to get your mind blown!)
“Filled a hole in my education that I didn’t know was missing. Incredible resources that are invaluable to my work and my personal understanding.”
“Hands down the best workshop I have ever attended. Has given me the tools to change the way our entire team works with data.”
“Finally there is something that is actionable. There is such a push towards equity but there hasn’t been a framing or a set of tools that actually work.”
This training includes:
• The Funding Web (an incredibly effective, no-cost method for revealing and rebalancing power dynamics in your project without pointing fingers).
• Motivation Touchstones (the core of every good data project where you clarify your priorities, definitions, and parameters in a useful, realistic, and equitable way).
• The Perspective Microscope (an invaluable scaffolding for designing equitable and waaaaaay better research questions).
• Data Biographies (or why crucial information isn’t “metadata” it is the data!).
• How to think about proxy variables, identity categories, and small sample sizes. (And how to talk about them too!)
• Identifying universal equity issues in descriptive, predictive, and causal analyses.
• How to talk to your data analyst about bias buried in their modeling. How to ask questions as a data analyst that can actually convey the meaning you’re working so hard to wring from your model.
• The Denominator Bracket (probably the hardest thing about data turned into the funniest game you’ve ever played (no joke we have people screaming with joy at their computer monitors during this one!)).
• Interpretation Matching (how to keep your definitions, context, certainty, and methodologies consistent and equitable from start to finish).
• The Reverse-Engineered Legend (a blow-your-mind approach to non-oppressive data visualization design).
• Checklists for Equitable Communication and Distribution in data reporting (or “how not to trip at the finish line”).
• AND MORE!
Note:
Not sure if this is the course for you? The Data Equity Primer is a prerequisite for this course and coincidentally it’s the perfect no-commitment way to find out what it’s all about and to spend an invigorating and empowering hour getting up to speed on the whole data equity thing; check it out here.
