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Each one teach one: how we’re practicing antiracism as an organization

This blog post outlines our working approach to practicing antiracism [1] as a community striving to bring data and power to the people. We at Data 2 the People firmly believe that the more openly we each share our learnings with each other, the faster we progress, and the faster we create the world we want. We believe we each have much to learn, and also that we each have something to teach. And so, as we forge ahead, let’s learn together and may

How we practice it concretely

Before we get started on specific steps, we first need to enumerate our principles for a fruitful practice of antiracism. These include: making a clear commitment to infusing this practice in everything we do; continually seeking to learn and iterating accordingly; being pragmatic in striving for progress, not perfection; maintaining low ego.

We believe it’s important to apply these principles to the following three areas, which are applicable to any organization:

  1. The team: It all starts with the people building the organization or community, so start with the team, with leadership modeling these principles and explicitly leading in normalizing discussion, action, and accountability.

  2. The work: Review how your line of work can be, and has historically been, racist (i.e. how it has assumed, even if non-overtly, supremacy or normalcy of one group over others, or unjustifiably privileged attention to one group over others), and test possible solutions to countering that.

  3. The industry: Communicate what you are learning from practicing antiracism to the broader community or industry, listen to what others are learning and sharing, and invite more people into the conversation and to take action.

Below are more details (non-exhaustive) on how we’re applying the above three-pronged approach at this time (and note, it is continually evolving!).

The team

Starting with the team is important because everything flows from the people. For a healthy practice, an organization’s commitment to antiracism/equity must be both top-down and bottom-up. Top-down, the leader(s) must lead by example in action and make explicit the importance of antiracism/equity to the team’s success. Bottoms-up, the broader team has to buy into and wholeheartedly recognize that antiracism/equity is critical to the team’s success, and to ensuring the most effective use of individual team members’ contributions.

Practicing antiracism/equity in building a team requires: recruiting people from a diverse range of backgrounds (racially and otherwise), fair assessment of candidates across backgrounds, equitable support of team members’ integration and growth after they join the team, and inviting the team to help us get better at all of the above. For us, that concretely looks like:

The work

Now, turning to the work we actually do. We exist as an organization precisely to help governments operate better and facilitate equal access to thriving for all. To help governments do this, we need to support and empower burgeoning leaders, organizers, and policy-makers who value and model equity. Here’s how we approach doing this:

The industry

We have no interest in being unique flowers in the industry regarding our insistence on equity, integrity, excellence, and truth-seeking. None interest whatsoever. Quite the opposite -- we desire for these to be industry norms. If another organization is modeling any of these better than we are, well, that will just push us to be better, and that’s a win! #eachoneteachone

Given our desired industry norms, we want to contribute to the ongoing conversation about racism and antiracism in the political data world. Hence this blog post. We also want to talk about antiracism explicitly in our conversations with campaigns, other political data science groups, with donors. Through these conversations, we can share ideas and learnings, and continue to learn, iterate, improve.

Now that we’ve shared what we’re learning and doing, what do you think? If you’re in the political world or political data world, we’d love to hear your thoughts! If you’re in a different industry or kind of community, how does the team/work/industry framework apply? Let us know! Let’s keep the conversation going, so we can grow with and learn from each other! May #eachoneteachone


[1] Our practice of antiracism is a fight against all forms of supremacy, i.e. any time any group or individual pursues their interests and desires at the expense of the agency of others. It is a fight for equity. It is a fight to build stronger communities, no matter their makeup; a fight for all communities to have the resources and the space to breathe, to grow, to learn.

[2] “Each one teach one” is a phrase I learned from a Black woman at a data science meetup back in 2016. I was struggling with something, I don’t remember what, and she helped me debug the situation. I sheepishly thanked her for her help, and she shrugged off my sheepishness saying the equivalent of, “Yeah, well I know you’ll be helping me or someone else with something before we know it. Each one teach one, you know what I mean?” It has since been verified by a personal Instagram-based survey (n=62...ish) that of all my Black and nonblack friends, only Black people have ever heard this phrase, and only from other Black people. In the spirit of operating generously, out of place of abundance, I share this phrase with you too, so that you, too, can incorporate #eachoneteachone vibes into your way of being, and collaborating/learning with others. You’re welcome!

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