How to spot a narrative pretending to be "evidence."

We work with the Data Lifecycle Framework in order to help us think about ways to surface inequity and increase the equity in every part of our data products. The interpretation step is a critical place to put our attention since it is often where the line between "objective result" and "subjective narrative" gets blurred. 

The Interpretation step of the data lifecycle is where data results are translated into meaning. When it comes to equity, distinguishing between the stages of results and interpretations is crucial. Results reflect the output of an analysis, *then* an interpretation explains what they mean. It can be difficult to wrap your head around which is which, so here's a little game to help you learn to distinguish.

Play the game here.
2020 In-Person Workshops
We're receiving lots of requests for in-person, hands-on workshops on how to embed an equity lens into your data products. We're offering workshops for researchers, executives, and public policy makers and political staff. 

We're in the process of finalizing dates and locations. We know for sure we're coming to the DC area, the NYC area, the Nashville area, the Miami area, the Vancouver area, the Ottawa area, and the San Francisco area. Details and dates coming soon.

If you're in any of these areas and want to let us know dates that work best for you or if you're in a different area and want to put in a request, please email Heather and let us know.
A Wonderful Thing This Week
A perfectly timed article on "Why Impact-Per-Dollar is a terrible, harmful way to measure nonprofit effectiveness" can be found here.

One of the main reasons is, of course, a lack of attention to equity. 

"It fails to take equity into account: IPD measurements often do not account for the fact that people from marginalized backgrounds are often more “expensive” to serve, requiring specialized services, translation/interpretation, transportation, childcare, etc. So then the organizations that serve marginalized folks will be seen as less efficient and thus less effective, which means donors will give less to them."
Data Amnesty
After a year of running pilots of our Data Amnesty salons, we're launching them full time for 2020. 

When I was a kid I used my local library constantly. And I often had books that were soooooo overdue. My library had Amnesty Day - when you could bring back any book and there would be no overdue charges. They wanted their books back more than they wanted the money on this day. The We All Count Data Amnesty Salons is that for data. There is no shortage of conversations encouraging the use of impact data, big data, geospatial data, mobile data, Bayesian analysis, data storytelling, and so much more. And this is great stuff. However, in such a world it’s often hard to know what you don’t know. And it can often feel scary or embarrassing to ask. You don’t want to be exposed as the only one who doesn’t know. Truth is, most of us are confused about something about data. Here’s your chance to ask anonymously or in person. We are holding regular live streams of the Data Amnesty Salons. You can submit questions via our anonymous link, email Heather questions, or ask questions live during the stream. Each month, Heather will answer a selection of questions. It’s part of our commitment to Demystify, Democratize and Demonstrate Data for Equity.

Our first Data Amnesty Salon for 2020 will be live on January 14, 2020
4pm GMT (11am Eastern USA, 8am PST, 10am CST, 7pm EAT)

We're looking for equity problems and successes.

If you have a story or idea you want to share, send me a note by replying to this email.

Project for Equity in Data Science
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