In Chapter 1 of Precision Journalism — what many consider to be the foundational text of data journalism — Philip Meyer wrote that in order for his vision to take off, first, editors would have to value the application of social science methods to journalism enough to develop in-house capacity. Hiring an outside consultant to feed a reporter data wasn’t enough — the reporter’s insight and ability to handle deadlines were key.

Then he wrote:

The second need, of course, is for the editors to be able to find the talent to fill this need. Many journalism schools are prepared to supply it. Some have faculty members with the necessary methodological skills; others are geared to directing their students to the appropriate courses in the sociology, psychology or political science departments.

Ooof. That was published in 1973. Interestingly, that passage was stripped out in later editions.

Hold that thought.

Fast forward to 1999. That year, the Poynter Institute called together 22 data journalism practitioners of the day — the children of Meyer’s ideas — and talked about how the use of computers and databases to do journalism had changed the practice. And how it hadn’t.

In a report called When Nerds and Words Collide: Reflections on the Development of Computer Assisted Reporting, Nora Paul summarizes the discussions in a bulleted list. I’ve got an original printing of this document on my desk, and I swear every bullet point is worth talking about. My favorite points, not surprisingly given where my paycheck comes from, are in the “Teaching/training” section. Compare Meyer’s confident declarations that journalism schools are here for it with Paul’s summary of the feelings of data journalists 26 years later:

Re-thinking journalism education — what should we expect from new journalists?

Integrating CAR into J-school curricula, particularly for undergraduates.

Improving journalism education to incorporate “advanced reporting” techniques and getting faculty interested in in CAR.

Teaching math skills to journalists and integrating number crunching with the the teaching of good storytelling…

Teaching conceptualization, application of “scientific” logic, and reasoning to data analysis.

I kinda have a thing for making angry predictions that things won’t happen. And it would be pretty easy to say, in the 20th year after Nerds and Words was published, that 2019 won’t be any different. You’d think 20 years and the obviousness of the importance of data skills in our modern world would be enough to get j-schools into the game, but you’d be wrong. Arguments that “if we add math to the curriculum, we’ll scare all the students away” are starting to feel eternal, the journalism-school equivalent to philosophical arguments about the nature of being.

I want to be positive, so here’s my prediction: Forty-six years after Meyer caused a ruckus by saying journalists would be less wrong if they embraced the mindset of the social scientist, 2019 will be academic data journalism’s Walden year. Those of us who care about this stuff are going to go off to a metaphorical cabin in the woods and think about what we’re doing. Deeply.

Thoreau even gives us a start.

I see young men, my townsmen, whose misfortune it is to have inherited farms, houses, barns, cattle, and farming tools; for these are more easily acquired than got rid of. Better if they had been born in the open pasture and suckled by a wolf, that they might have seen with clearer eyes what field they were called to labor in.

I feel like it’s time for the academic data journalism side of the house to dive into and embrace the academy more deeply. We need to spend more time in discussions about epistemology and the philiosophical problems of knowledge — and at the same time, we need to be hanging around with the digital humanists analyzing huge corpora of text for insights. We need to get into the weeds of the psychology of corrective information, crash as many data science or bioinformatics classes as we can, and scour every lab and lecture hall for new ideas that can be applied to telling stories about our world.

And from our time in the cabin, we need to write it all down and put it in the open. What’s the point if we do all this and bury it in a paywalled journal no one will read? I want the academy to lead on new and interesting techniques. Currently, it’s the other way around. A publication does something interesting with x, and suddenly there needs to be a module in a class teaching x.

It’s time for data journalism on campus to show the way to something new. We need more Phil Meyers. We don’t need to wait nearly half a century to get it.