To Jargon or not to Jargon

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Contributed by Elisha Wood-Charlson

Jargon, as defined by Google, consists of “special words or expressions that are used by a particular profession or group and are difficult for others to understand.” So, you can imagine why jargon is a natural target for science communication training and workshops. Hey, science jargon even has its own April Fool’s spoof article.

Well, as it turns out, defining jargon and identifying jargon create a bit of inherent irony. A word is only considered ‘jargon’ when it isn’t well understood, so when are science words ‘jargon’ and when are they not? Google’s definition suggests that jargon can be specific to a group, and not necessarily restricted to a technical field. In addition, Google gives the entertaining synonym of “slang”, which begs the question – are scientists actually speaking our own form of “Science Jive”?

One of the most challenging parts of science communication is understanding your audience well enough to choose vocabulary that will communicate your science accurately while still getting your message across. Therefore, we need to start thinking about our “Science Jive” in layers. How far removed is our target audience from our science field?

The Russian Doll of Science Jive
Nesting Dolls (Photo Credit: James Lee)

Nesting Dolls (Photo Credit: James Lee)

As with all science communication efforts, you must first understand your audience(s) before you determine how much jargon you can layer on. The smallest, innermost ring is your peer group (you are the doll in the center). Your peer audience will include members of your lab group, your collaborators, and even your fellow participants in a domain-specific session at a conference. Almost everything in this ring may be considered jargon to a general audience, who resides in the largest, outermost doll layer. And, although some of the jargon translations from the far inner ring to the far outer ring may be the most challenging (discussed later), the dolls in the middle are where things get really interesting. How well do you know your audience two rings removed? For example, I recently attended the 2015 AAAS conference in San Jose, CA. Having never attended an AAAS conference before, I was surprised at the breadth of science topics presented. They ranged from looking at the effect of epigenetics on the brain to 3-D printing of 4-D mathematical models to microbial oceanography, my personal ring of Science Jive. So, how do you know when to jargon and when not to jargon?

The best way to figure out your audience is to understand where they exist in the science communication space. Do they read popular science articles, like those in Scientific American or Discover? If so, getting familiar with those journals (if you aren’t already) will help you determine which jargon level you should speak to. For example, in situations where “addition of viral concentrates resulted in decreased photosynthetic activity” might not work, something like “after adding more viruses, the cultures started dying” might be perfect. From another perspective, if you are writing something for a government office, you might consider getting in touch with whomever is in charge of science-related issues. Depending on their background, they may only be one or two jargon rings away. Or, if their background isn’t in the sciences, they may comfortably reside in the far outer general public ring.

Communicating Science Jive to the Outer Doll

Have you tried explaining your research to a family member? Megumi Chikamoto had a great post (4 Feb 2015) on Real Science at SOEST! blog about jargon, relating to her 7 year old son and making her message more understandable to a broader audience.

Translating jargon takes a bit of trial and error. Pick a prominent jargon word in your specialization and start trying out alternative vocabulary with the lab down the hall, fellow students at a departmental seminar, or with other science departments that meet up for pick-up soccer games after work. In the end, you may still end up with a word(s) that can’t be captured at the level of accuracy you require. Another strategy is to develop an analogy for your research. Can you capture the dispersal model or biogeochemical flux pathway in a metaphor or image? For example, Donn Viviani, a graduate student in C-MORE, is able to transform his research into the simple process of making a cup of tea!

In the end, only you can decide when to jargon and when not to jargon, and it will take practice. However, there should also be a collective effort by every science specialization to establish some translated terms that are acceptable replacements for their domain. In some areas, such as climate change, this is already happening. But we shouldn’t wait for a social movement to motivate us! Scientists are people too, and we should be making an effort to communicate using language that can be understood by our audiences.

 

Other resources
Scientific Jargon, Thompson Writing Program handout by Jordana Rosenberg 2012
Terms that have different meanings for scientists and the public, log post by Andrew David Thaler at Southern Fried Science
Words Matter, AGU blog post by Callan Bentley


Elisha M. Wood-Charlson has a PhD in marine science, and has worked in a variety of research areas including coral symbioses, marine viruses, and viruses in corals. She is currently testing out life as a science communicator and is finding the creative latitude enjoyable. She works for the Center for Microbial Oceanography: Research and Education (C-MORE) as an educator, designing #scicomm training for graduate students, postdocs, and early career researchers (check out the new Science Communication Portfolio training guide on the SOEST website!). She is also managing the EarthCube Oceanography and Geobiology Environmental ‘Omics (ECOGEO) Research Coordination Network (RCN), which demands structured communication between the scientists asking the difficult ‘omics questions and the bioinformaticians making the tools to help answer them.

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Bedtime Science Stories

Contributed by Megumi Chikamoto

Every night, while sitting beside my 7-year-old son’s bedside, I ask him one question.

“What did you do today?”
“Work,” he replies, briefly. Sometimes he says, “math,” or “recess.” Some days, he turns to ask me the same question.
“Mommy, what did you do today?”

To answer his question, I try to explain one of my current research projects in detail. When I talk about the basic theory or hypothesis of my scientific topics, my son is really interested. Specifically, I have succeeded in catching his attention by talking about the drastic changes in marine plankton species that occurred around 15,000 years ago. After listening to my explanation, he comes up with his own hypothesis, which he tells me excitedly. This conversation with my son is much like brainstorming with my colleagues, and I am impressed that my son understands the big concepts of my research. But one night, I decided to take it one step further by explaining the modeling concept of my research. He fell asleep before I finished my story.

I often face this problem when I talk about modeling simulation to the general public, like my friends or relatives, not just my son. People, especially those living in Hawaii, surrounded by the ocean, tend to have a stereotypical image of oceanographers, thinking that we go out to sea for our research. I am an oceanographer; yet, I do not go out to sea. Instead, I sit down in front of a computer, peer at a screen, and write programming codes for over 6 hours everyday, 5 days a week. When I explain this to my friends and relatives, this unexpected research style seems to intrigue them, and they ask me to tell them more about my research. My research approach is using an Earth system model that is a numerical tool for calculating time evolution of the global climate system. The model calculates the atmosphere and ocean phenomena, such as wind blows, ocean currents and precipitation. Furthermore, the model includes components of marine ecosystems such as tiny plankton. My target is to elucidate marine ecosystem processes that link to climate change. But when I describe a model in such a way, my audience, like my son, loses interest quickly. This is one of the reasons why I want to improve my skill of public speech.

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Map of present-day phytoplankton biomass in chlorophyll concentration in an Earth System model. Image Credit: M. Chikamoto

One thing I realize now is how much jargon my explanation contains! Due to the specialized words, my audience might hardly understand the basic concepts and their attention is lost. Generally, people prefer to relate to a personal story, or sometimes an emotional one like in a novel; no one cares about the specialized issues (if someone is very interested in the specialized issues, he/she might be close to being the expert!). I know now that I should avoid describing my research like a scientific presentation, which is what I have done so far. Rather, I need to focus on the storytelling during an interactive conversation. Without more ado, I will try storytelling.

Why do we simulate?

Just think about this. If you take photographs in sequence with a camera and then want to know what is happening between the photos, what do you do? You might convert these intermittent images to an image sequence by taking the gaps and try to predict what happened in between in your brain. I do similar things in my research. Oceanographers monitor signals of ocean phenomena when going to sea, but getting the data is like one photo snapshot at a time. In order to display an image sequence like you do in your brain, I simulate it using a computer model instead. The model simulation in the computer calculates the time evolution of the Earth environment. By analyzing the simulated results, I can know what is going on in the environment. In fact, I use many kinds of models for today’s environment as well as for the past or the future. Through past, present and future climate simulations, I want to know mechanisms of the earth systems – how the earth systems of several different rhythms play harmony.

Trying again

One night, I decided to try explaining model simulation to my son again.

“I simulate the Earth environment using a computer and study what is going on in the atmosphere and the ocean. When I was a college student, computers were very slow and we were waiting to finish the calculation for several months. But nowadays, technology has developed tremendously and computer speed is much faster than it was in the previous era. For example, my computer can finish a 500-year-long simulation while you are sleeping at night. In this way, we can go back to the past using very long simulations, even as far back as to the Ice Age. Using a computer, I can study all of the past, the present, and the future climate.”

“That’s great!” my son said, admiringly.

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Megumi O. Chikamoto is an affiliate researcher in SOEST and a postdoctoral researcher at International Pacific Research Center. After getting her Ph.D in Atmosphere and Ocean Science at Hokkaido University in Japan, she has worked at the University of Minnesota, the University of Tokyo, the Japan Agency of Marine Science and Technology, and then the current position.  Her research focuses on marine ecosystem response to climate variability and changes in the past, current, and future.