The perils of technical jargon

by Adam Brownsell

As the editor of a forward-thinking, customer-centric media brand, you might expect this article to be a beacon of clarity, demonstrating positive values, the profit of learnings, and leveraging best practice in content origination to take reader engagement to the next level.

Or, as an editor of a magazine, you’d think I could write well because of my experience in the field. Jargon. We encounter it daily and, depressingly, recent research has shown its use is increasing in academic literature.1 The authors conducted a statistical analysis of over 700,000 article abstracts from 123 journals in PubMed covering a range of disciplines. They used two measures of readability – the Flesch Reading Ease (FRE) and the New Dale-Chall Readability Formula (NDC) – to answer the primary question of whether readability is related to the year of publication. Lower readability is indicated by a low FRE score or a high NDC score.

In making communication between experts as effective as possible, jargon can render it utterly ineffective for everyone else.

I’ll admit to not understanding the formulas in the next part, but I’ll include them because I assume many of you reading this will: The research shows a strong decreasing trend in the average yearly FRE (r = -0.93, 95% CI [-0.95,- 0.90], p <10-15) and strong increasing trend in the average yearly NDC (r = 0.93, 95% CI [0.91,0.95], p <10-15). I’m reliably informed this means we can be pretty confident that the data supports the conclusion that scientific articles are getting less readable – and more jargon- filled – over time, with recent examples being the worst.

Of course, we have also encountered jargon in the paragraph above. It’s not just about drinking lattés in trendy bits of London and musing about ethical beard wax; jargon has a somewhat valid role to assist specialized communication. Even that semicolon could be thought of as jargon (Kurt Vonnegut quipped that “all they do is show you’ve been to college”). But in making communication between experts as effective as possible, jargon can render it utterly ineffective for everyone else. This is problematic for those of us who work in science communication – we not only have our own knowledge gap to cross but also that of our reader. We can play along and play to the crowd (see my clumsy attempt in paragraph three), but we might end up revealing our own ignorance and grubby motives in the process.

George Orwell wrote: “The great enemy of clear language is insincerity. When there is a gap between one’s real and one’s declared aims, one turns as it were instinctively to long words and exhausted idioms, like a cuttlefish spurting out ink.” He’s spot on about the inkiness, and a solid case can be made for ickiness as well. At a time in our political history when we are supposedly post-truth and seemingly pre-apocalyptic, the importance of saying what you mean, meaning what you say and being understood has never been greater. The scientific method that took us from hunter-gatherers to data gatherers is now being used against science to erode trust in evidence and data. Studies show that red wine both prevents and causes cancer. Studies show that humans are both the cause and the blameless victims of global warming. Studies show that low interest rates are both beneficial and harmful to the economy. How can you trust science when it can’t even agree with itself? As the public struggles to reconcile contradictory “facts,” it is easy for those with agendas to either pick the bits they like or dismiss the whole affair as ridiculous because the left and right hand seem ignorant of each other.

Let us remember that we should be able to explain the biggest of ideas with small words and modest intent.

The underlying problem here is the lack of public understanding of scientific method – the role of challenge, consensus and weight of evidence – the plausibility of the hypothesis that best fits the evidence, and how often and in how many scenarios it can still be shown to fit. I should imagine that readers of this magazine, being experts in statistics and data, are confronted often by those who want to be proven right, who present a compelling narrative and just need the data to support it. The more tenuous the claim, the more convincing the story needs to be. Unfortunately, as the authors of the research above discovered, this worrying habit of demonstrating how important something is through a purple vocabulary is happening even when the science is good. My concern is that this isn’t confined to the literature, and we are further isolating people from evidence and scientific endeavor by allowing a wall of words to obfuscate what we really mean, and what really matters. Interestingly, it looks like we seek out plain-speaking sources even if we don’t play by those rules ourselves. An MIT Sloan Research Paper showed that Wikipedia – the enormously popular but rarely cited information repository – is shaping the language that researchers use in papers.2 Ideas, words and phrases that are incorporated into a Wikipedia article subsequently appear more often in scientific literature. The authors go on to suggest that “increased provision of information in accessible repositories is a cost-effective way to advance science.”

We’re at a time when we need the scientific community to be as open and as inclusive as possible. Anyone, if asked, would say they despise jargon, yet we all use and abuse it on a daily basis. We’ve all written papers that are effuse with lofty sentences, and we’ve all derided others for doing the same. I think we all understand the need for scholarly communication and its complex vocabularies and expressions. Disciplines like mathematics, chemistry and computer science demand whole new languages to illustrate ideas that cannot be expressed in our mother tongues. But, through all of this, let us remember that we should be able to explain the biggest of ideas with small words and modest intent. If we let jargon get the better of us we harm progress, debate and make our ideas and intentions opaque.

So, let’s all find the bandwidth to action a stepladder strategy toward a new paradigm of customer-facing dialogue and disintermediate the jargon. It’s a win/win.

References
  1. P Plavén-Sigray et al, eLife 2017, DOI: https://doi.org/10.7554/eLife.27725
  2. N Thompson, D Hanley, Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial. MIT Sloan Research Paper. Available at https://ssrn.com/abstract=3039505
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