No one likes reading academic papers. Deep down even scientists hate reading academic prose. Aside from the rare gems now and again, academic prose is dry, terse and quite convoluted. This state of affairs is not surprising to anyone – it is so widespread that we have grown to expect bad prose and stumbling upon good writing in science feels like a slap in the face. It energizes and wakes us up. Whatever you may think of academics like Noam Chomsky, Jerry Fodor, Steven Pinker or Douglas Hofstadter, there is no denying that they have the uncanny ability to pierce with their words. Just look at some of the examples below and tell me they don’t intrigue the hell out of you.
Fodor, for example, entices the readers of his Precis to the Modularity of Mind (1985) with the following opening paragraph:
Everybody knows that something is wrong. But it is uniquely the achievement of contemporary philosophy – indeed, it is uniquely the achievement of contemporary analytical philosophy – to have figured out just what it is. What is wrong is that not enough distinctions are being made. If only we made all the distinctions that there are, then we should all be as happy as kings. (Kings are notoriously very happy).
Similarly, you can’t help but wonder what Hofstadter’s arguments will be when he makes a statement such as:
Analogy is the very blue of the sky of cognition. It is the talent so fundamental that it fuels our minds. [..] Is it irrational, subjective and concrete? Yes indeed, but it is also the underpinning of rationality, objectivity and abstraction. Analogy is not a rare luxury of thought or an exotic, remote corner of cognition. Analogy is the entire transport system of thought, including motorways, roads and trails; it pervades thinking, from throwaway remarks to deep scientific and artistic insights. All along the spectrum, analogy lets us see the new in terms of the familiar. It guides us in learning new concepts, solving mathematical problems, dealing with interpersonal conflicts and making political decisions.
– The Forgotten Fuel of our Minds, 2013
Why are examples such as these so few and far in between? Why are academics, who live and breathe writing, so notoriously bad at it?
In his recent essay, Why Academics Stink at Writing, Steven Pinker suggests that it has nothing to do with a conscious desire to be obtuse in order to put meaningless content behind a veil of jargon. Or with the fact that academic journals and reviewers expect papers to be written in what he calls academese. Nor does academese spring from the fundamental abstractness and complexity of the subjects we study. At what then, can we point our fingers to, as the agent that poisons academic writing?
The trap of self-conscious writing.
One problem with academics is that when it comes to writing, they are like a ship-wreck survivor standing on two planks in the water that are moving in different directions. Academics are torn between satisfying two different purposes when they write – one is to inform their readers of novel data or ideas. At the same time, however, academics agonize over how they will be perceived in the eyes of their colleagues. Will they be thought of as careful, knowledgeable, creative and analytic? Or will they be dismissed as hacks who go beyond the data in making conclusions, who disregard their colleagues’ work, however remotely related, as people who are way too confident for their own good?
Pinker sees this trap of self-conscious writing as one of the fundamental causes of bad writing. It leads to metadiscourse (e.g. “This article is organized as follows”), to using vacuous qualifying phrases (e.g. almost, quite, in part), nominalizations where verbs would suffice (e.g. “The affirmation of the current hypothesis by the data…”), etc.
But even if one solves all of these local problems, academic prose might become easier to read, but wouldn’t necessarily become any more engaging. More often than not, academic papers lack spice, they lack a compelling story.
We should all be storytellers.
Why do people enjoy reading fiction? I’m sure there will be as many different answers as there are readers and writers, but I believe that the cornerstone of all is good storytelling. Even the most fascinating characters or the most beautiful prose can be empty shells when they are built around bad, misdirected, and unsatisfying stories. Lolita, for all its beauty and charm, is one unbearably boring book (don’t crucify me, please!).
Most articles in science lack a compelling story. Data by itself is meaningless, and yet, most academics, including me, often treat it as self-explanatory, as something that should enlighten readers by its sheer awesomeness. But we don’t care about data. We don’t care about numbers. Numbers are just tools to describe the world.
Scientist care, or at least they should, about what those numbers can tell us about the fundamental properties of reality, the reality of the natural world, of our minds, and of the culture our species has produced. And this is fundamentally a storytelling issue – what does the data tell us about that specific aspect of the world? How did it come to be the way it is, how does it work, and how can we fix it, if it is broken? How do I, as a scientist, share that story with my peers and with the public?
Jeffrey McDonnell, in a paper published in Nature a few days ago, deals with exactly this issue. While above I have treated it as a problem for readability, he aptly recognizes that the lack of storytelling ability is what fundamentally makes writing a challenge for many academics. He uses a storytelling approach to help him and his students write better, clearer and more engaging academic papers:
Each of my group’s papers now starts with a storyboard session at a whiteboard. I pretend to be a big-time Hollywood producer and ask the Ph.D. student or postdoc to play the role of would-be movie director pitching a new movie to me. Their pitch must answer three questions: What is the status quo? What is wrong with the status quo? How does this new paper go beyond the status quo?
This approach helps frame the story and place key figures and technical findings in context. Balancing each of the status quo elements is a great way to set up the introduction—often the toughest section for early-career scientists to write—and to lead the reader to the research questions or hypotheses.
I myself, realized that this is the way to go about three years ago, when I was struggling to write one of my first papers. I believed I had something important to say, but I found that I have no idea how to stay it – I became paralyzed every time I stared at the cursor blinking on the empty page.
My breakthrough occurred, similarly to McDonnell’s, when I realized I should start asking those precise questions – what is my data telling me? Not what have I found, but what does it mean? What is the main conflict that my data resolves? How do I build up that conflict in a way that makes the reader ache for the resolution?
I picked up those techniques not from anyone I know, or from a course on academic writing, but from a book on writing fiction, where story is king and reigns supreme. I am far from being any good at it, and I often fall back on bad habits, but I’m constantly trying to improve.
The problem is, in STEM and in the social sciences, we rarely teach writing in undergrad or grad school. Rather, it is expected that writing is something students will pick up on their own as they go, as they read more and more. Given that the papers they read suffer from all the vices of academese, this expectation is unrealistic. We need to teach ourselves, our peers, and our students, how to write better stories, because stories do not tell themselves, and data is impotent when buried in bad writing.
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