Navigating the world of science communication can sometimes feel like convincing people to eat their vegetables. But nobody seems to agree on which part of the process – the story or the science – is the metaphorical vegetable. Some academics hold their noses as they force down the unpalatable concept of embracing narrative. Other outreach folks are convinced that hiding science in other things, like adding pureed squash to spaghetti sauce, is the best approach. They make the argument of, “They won’t even notice, and it will be good for them!” Maybe it’s because I love science and stories (and vegetables), but I feel like both sides are getting shortchanged.

There is more to narrative than just writing, “There once was a tiny bacterium, whose presence caused a wild delirium.” And kids have an admirable appetite for the nitty gritty, when motivated. Just use the wrong dinosaur name in front of a preschooler to get a glimpse into their capacity for taxonomies, long words, and esoteric practices. The result will feel shockingly familiar to anyone who has ever mis-stated a research finding in front of an academic.

Yes, targeting scientific content for new audiences takes work. It takes work to get a sense of what your reader does and does not already know. It takes work to learn the difference between simplifying your language and simplifying your science. And it takes work to figure out why each audience might care about your research and then frame the findings in that context. It is much easier to put your data out there, stand back, and say the results should speak for themselves. But here’s the thing. The process of getting from results to meaning also takes work. It takes work to understand how and why data are collected a certain way. It takes work to figure out what those data even represent. It takes work to know what those results mean in a bigger picture. And it takes work to figure out what those results should motivate an audience to do, think about, or feel. If your goal is for your audience to come out understanding something new, you have to decide who is going to have to put in the work to make that understanding possible.

Academic conferences can provide excellent examples of the most extreme cases of just putting results out there to speak for themselves. The audience is meant to be made up of fellow experts, after all. But many researchers also know what it is like to struggle from the other side of the podium. You wonder how much effort it would have really taken to make sure that each axis was labeled in a legible font – or even labeled at all. How much effort would it have really taken to give a two-sentence description of the difference between the new sampling method and the old one? How much effort would it have taken to realize that 31 slides would not fit into an 11-minute talk?

The implicit assumption seems to be that the time and effort of the person speaking is far more valuable than that of the person trying to learn. And because this style of communication is so often the norm, that assumption is made without the alternative even coming to mind. So it is easy to understand why those same assumptions can make targeting science communication to new audiences fall into the same traps. But anyone capable of learning to splice DNA or fold single sheets of graphene is capable of thinking about new information from the listener’s perspective.

Career academics and young learners may be on opposite ends of the spectrum as far as expertise. But these are two groups that, when properly motivated, can show shocking levels of persistence for mastering a new skill. Once we accept that framing research in a narrative does not mean giving your data cartoon eyes and a tragic backstory – and once we stop assuming that kids want nothing more than chunky graphs in primary colors – we can start to close the divide. And when we slip up and send our university bio to a first-grade teacher, we have to be just as willing as we expect kids to be to learn from our mistakes.