The Power Dynamics of Data Jargon

Early in my career, I was working on a project using education data, and we were having a meeting with policymakers, school principals, and a team of researchers. When one of the principals asked a question about what assumptions were used in crafting one of the models, I was perplexed when the lead researcher launched into a long speech chock full of vague, unusual and complex jargon. Why would he do this? I knew that it wasn’t because the researcher was unable to discuss these ideas in simple, clear language because we had had many easy, plain conversations together about this very question. What was going on?

I would soon come to recognize this as an extremely common equity issue in data. This researcher felt attacked (or at least challenged) and so he unleashed his favorite power move: Jargon.

When I say “jargon” I mean technical and pseudo-technical words and terms used in data science. Jargon can be used to give power or hold power.

Sometimes using a precise and technical term is the best way to communicate an idea in data. These are important words that are worth explaining to our colleagues, clients and audiences to increase clarity and data literacy for everyone involved in our work.

Good data jargon gives power to our stakeholders because it reveals important concepts that are at the heart of our…