The Privilege Embedded in your Unit of Analysis
How much water per bouquet? If we watered them all using the average required per bouquet, we’d over water one and underwater one. What’s the problem: we’re using the denominator of bouquets instead of flowers.Defining your denominator is as important as defining your...
Tools in the Wild!
Seeing others putting things into practice is one of the best ways to learn how to go from idea to real meaningful change in our data work.
Motivation Touchstones Part 3: Definitions
A well-crafted Motivation Touchstone contains your success criteria and aimed-for rewards, as well as a summary of the major restrictions and parameters that your project faces. These elements give us its outline, the scaffolding required to make decisions throughout...
A Great Way to Think About Data Science: The Bowtie
One of the best ways to talk about some of the equity challenges posed by the data science process is what we like to call the “bowtie”. The ends of the bowtie are almost always broader than the knot at the center, and it’s how you tie the knot that keeps the bowtie...
Holiday Poster Drop!
It's that time of year again: We All Count's creative director has worked up 5 new data equity posters and they are awesome! What started as an outlet for him to vary from our color scheme has blossomed into our new favorite tradition. Click here to buy one for...
Measure Upstream Discrimination
When we try to measure gaps in outcomes between groups, we often turn to an approach called a Blinder-Oaxaca Decomposition. I’m all for identifying discriminatory gaps, but we need to be careful that we don’t discount certain kinds of discrimination from our data...
Crafting Models for Equity
Author’s Note: This is going to be a long piece, but if we can get this concept down we’ll learn a way to embed our equity priorities deep, deep into the mathematical heart of our data work. Let’s go. The Model: A reflection of the world as the modeller understands...
The First Step in Equitable Predictions
When we use data to predict something, there’s more than one way to improve the equity of that process. The one that we usually start with is setting a tolerance level for the gap between the group our predictive model works best for and the one it performs worst at....
Motivation Touchstones: Rewards
When it comes to data projects, one of the most powerful tools we use is what we call a Motivation Touchstone. It’s a document that you and your team can return to over and over for guidance when figuring out how to make effective and equitable decisions at every step...
We Need to Fill in the Blanks in our Social Identity Data
Everytime I see a stat like "25% of respondents are Black", I see only one piece of a four-piece puzzle filled in. With only this piece, I don't know how to use this information. I don't know if it matches the category from my dataset, I don't know if it reflects how...