Jeffrey Alan Johnson of Utah Valley University is the most thoughtful and brilliant practitioner of institutional research I have read in years. This essay touches on issues of data and information that few people really think about. His discussion of the translation regime process of data systems is spot-on.
In this current essay he says:
Data scientists do not often think about our practices as political in nature. But all of the work required to represent some reality in a data system makes data inherently political. Especially as data-driven decisions become norms—even mandates—data scientists are creating the abstract world in which decisions taken place before being implemented in the real world.
The immediate sense in which data translation is political is that the choices made in translating data allocate political power in the real world, not just in the data set. Those who create the translation regime determine which groups do and do not exist, what concepts are available to pursue claims on institutions, which needs can be legitimized and which can be dismissed. The ability to make one’s self, one’s group, and one’s interests legible to the state, organizations, or other individuals is increasingly determined by where one stands in the data.
This is all absolutely true.
But there is another truth. The politics of information are such that those of us in government who oversee large data systems, as I do, often have to be mindful of the potential for misuse and abuse. We also try to focus on what the state (in my case) needs to know.
Over a decade ago, We made two decisions – allow “unknown/unreported/unspecified” as an option for gender reporting to us, and a second decision to go no further than that. We discussed a variety of other options at length and came to the conclusion that the state did not need to know. We felt, given some of the pressures we experienced in 2002 and even 2003, and the political climate, the time was not right to collect something by name and SSN that was not needed. We also kind of felt that it was really none of our business.
Virginia has very strong privacy laws, stronger than FERPA. But laws can be changed. They do so all the time. I’ve written enough law to be oh-so-very aware of this. I can’t reveal what I don’t know, what I don’t collect, which means I can’t cause certain groups of people to be targeted.
For now, it is kind of a trade-off between the power of being noticed and the comfort of not being able to be targeted.
The power to define is tremendous. For about 20 years in the institutional research profession I have defined my role as “teaching people how to count to one.” This is the essence of the translation regime because the distance between zero and one philosophically orders of magnitude greater than the distance between one and two. Defining what you count, who you count, is everything.
Knowing when to change the definition of one is understanding the politics of information and expressing a readiness to deal with consequences. Every decision I make about defining how to count to one ripples down to nearly 80 institutions and often causes them to change policies. Each decision also begs the question, “Why? Why does the state need to know this and what are you going to do with the information?” Bernard Fryshman is a master of asking these questions of USED.
In my normal mode of obstructing bureaucratic wastes of my time, I challenged the state IT agency over and over again about some of the information they were requesting for the IT strategic plan.
“Why do you need this?”
“We need to know scope of things so we can manage it.”
“Are you going to use it to recommend more IT funding for my agency?”
“No, we don’t do that.”
“What does manage mean – are you going to cut my budget?”
“Why no, we just need to know so we can manage it, to control it.”
“If you aren’t going to add to my budget, or maintain the funding I need to provide the services you mandate, you can only cut my budget, right?”
The politics of information matter. A sensitivity to upstream demand and control is often needed. The decisions about who and what to count are a balancing act.
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