What comes to mind when you read the phrase “semantic dark matter of scholarship”?

For me, it’s a roomful of monks engaged in some esoteric or alchemical pursuit, hunched and scribbling furiously.

David Krakauer, president of the Santa Fe Institute, introduces the concept in the institute’s winter newsletter as “the invisible factors and processes that make models and theories work in a given context without threatening their basic assumptions.”

It’s the stuff that gets abstracted out of the model for neatness’s sake but which has to be in place for the model to work. Evolution by natural selection is dark matter for the second law of thermodynamics: stuff keeps getting broken, but also, stuff keeps getting more complicated. 

In the push to translate neatly between one theory and another—like quantum and classical physics—we leave out a lot of messy context. When that messiness becomes too much to ignore, we set off in search of new theories.

If you’ve been reading for a while, you’ll know I was thrilled that Krakauer pivots from evolution and game theory to translations of Homer and Flaubert.

In the case of literature, semantic dark matter is the context that’s present in the author’s head but doesn’t make it onto the page. In discussing a translator who read every one of Flaubert’s reference texts before translation Bouvard and Pécuchet, Krakauer notes, “a great translation needs to wrestle with Flaubert’s semantic dark matter since these ideas are . . . present to some degree in the minds of his contemporary readers.”

In other words, it’s important to get a sense for what Flaubert was thinking insofar as it helps you understand what meaning his audience would have made from it. What’s being translated, then, is the experience of the audience, not the literal meaning on the page.

Think of absurd-sounding translations that emphasize etymology at the expense of cultural context (Krakauer gives an example of “cheeseburger” translated as “cheese in Hamburg”). Or take the experience of reading Shakespeare with footnotes compared to without: the addition of a little dark matter makes it that much more enjoyable.

Science communication, itself a form of translation, involves more than faithfully transcribing facts while “dumbing down” the language.

We need to understand at least a bit of what the scientists reading the paper already know—enough of their semantic dark matter—so that someone outside the field can appreciate why it matters.

And the findings must be put in a human context, so the audience can understand why it’s important to map the molecules in a painting from 1690, for example, or why we might want to synthesize ethanol from CO₂ and water.

And this, of course, is why we also need to know what weird, spooky semantic dark matter might be lurking in the minds of our audience. 

P.S. If you’re grappling with the semantic dark matter in your own research, I’m looking for a few beta testers for science communication coaching to help researchers articulate why their work matters. We’ll use strategies I’ve developed over years working with op-ed authors and helping speakers prepare for TEDxNewEngland. Learn more here, and please share; I’m offering three slots at half price in exchange for helping me build something truly useful.