This course teaches scientists to become more effective writers, using practical examples and exercises. Topics include: principles of good writing, tricks for writing faster and with less anxiety, the format of a scientific manuscript, peer review, grant writing, ethical issues in scientific publication, and writing for general audiences.
8.3: Writing for general audiences
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Writing in the Sciences
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8
Unit 8 reviews communication with broader audiences. You will learn how work with the media, be interviewed, conduct an interview, and write about science for general audiences.
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Dr. Kristin SainaniAssociate Professor
Health Research and Policy
In the next few modules,
I'm going to talk about communicating directly with general audiences.
In this day and age it's important for scientists to engage with the lay public.
Even if you're not planning a career in science writing, you can learn a lot
from the techniques that science writers use to engage the lay public.
I'll start with some tips for writing for general audiences.
First of all, I want to make clear that regardless of audience,
your general prose style should not change.
You're going to use the same principles of good writing that we talked about
in the first half of this course.
Try to be as concise, clear and engaging as possible.
But there are a few things you need to do differently when you write for
general audiences, rather than scientific audiences.
I've identified six skills that I think are the keys to writing for
general audiences.
I've laid these out here and I'm going to go through each one of these,
in turn, in a minute.
To have some examples to work off of,
I took excerpts from the abstracts of two scientific articles.
One from nature and one from science.
And I wrote lay summaries of these excerpts.
I picked these because I think they're pretty well written for
a scientific audience.
But I'm going to show you what I do differently when I write for
general audiences.
The first one reads.
Here we leverage the wide usage of smartphones with built-in accelerometry to
measure physical activity at the global scale.
We study a data set consisting of 68 million days of physical activity for
715,000 people,
giving us a window into activity in 111 countries across the globe.
We find inequality in how activity is distributed within countries and
that this inequality is a better predictor of obesity prevalence
in the population and average activity volume.
My lay summary reads, researchers used data from smartphones to look
at the walking habits of 717,000 people from 111 countries.
Countries with the widest gaps between the most active and
least active people also had the highest obesity rates.
Surprisingly, this activity inequality
was a stronger predictor of obesity than total amount of activity.
You can hear the difference between those two.
In a minute I'm going to walk you through how I got from the first version to
the second version.
The second example reads, atmospheric water is a resource equivalent to 10%
of all fresh water on all lakes on Earth.
However, an efficient process for capturing and
delivering water from air, especially at low humidity levels has no been developed.
We report the design and demonstration of a device based on a porous metal organic
framework that captures water from the atmosphere at ambient conditions
by using low-grade heat from natural sunlight at a flux of less than 1 sun.
This device is capable of harvesting 2.8 liters of water per kilogram of MOF daily
at relative humidity levels as low as 20% and
requires no additional input of energy.
My lay summary is, scientists have created a device that can pull water out of air.
Water-harvesting devices have been built before, but they were impractical for
everyday use because they only worked on extremely moist air or
required high amounts of energy to run.
The new device contains a porous crystal called a metal organic framework
that soaks up water vapor like a sponge.
A small solar panel provides the energy needed to condense the water into liquid.
A prototype containing two pounds of the crystal extracted 12 cups of water from
desert air in one day using only sunlight for power.
Again, you can hear the difference between those two.
When you're writing for general audiences,
the first thing you need to do, is you have to start with the take-home message.
You have to tell your readers the most important thing first.
If you don't tell them why they should care, then they may not read on.
This is not a hard skill to master.
But it's not the way that we're used to writing in science.
In a journal article, we usually start with the background and
then we build up to the take-home message.
When writing for general audiences, you have to flip this.
For example, in the one on the water harvesting device,
the scientists started with some background information about the amount of
fresh water available in the air but that's not the crux of article.
The article is about the device.
So I started my lay summary with,
scientists have created a device that can pull water out of air.
That's the key accomplishment.
And notice that I didn't have to embellish this or
give a lot of background information.
Lay readers will get why this is important.
Everyone knows that clean water is a scarce resource.
So if you can pull it out of the air, that would be an important breakthrough.
The second skill is that you need to recognize and avoid jargon.
And this is hard for scientists, because we are so
immersed into science, we don't even recognize half the jargon we use.
And by jargon, I don't just mean technical scientific terms.
But just the general way that scientists speak,
a lot of the way we talk in science sounds unfamiliar to lay audiences.
I teach a short summer course to graduate students and
post docs at Stanford, who want to learn to write for general audiences.
For their final assignment, they have to write a story for the lay public.
And even though they are trying to write for
the lay public, inevitably their pieces come back riddled with jargon.
So on their first drafts, I go through and I highlight all the words and
phrases that are jargon to a lay person.
And it really takes me pointing out the jargon to them
before they even start to recognize it as jargon.
For example, if you look at the one on the physical activity,
it might seem like this abstract is accessible to a general audience.
Because the authors didn't use a lot of fancy words or technical terms.
But, in fact, a lot of it is written in scientist speak.
So leverage, wide usage, accelerometry,
even the work physical activity is a more science way of saying exercise.
Global scale is distributed, prevalence in the population, average activity volume.
Lay people don't talk about activity volume.
They might talk about activity duration or the amount of activity, but
not activity volume.
So all of this sounds like jargon to a layperson.
The second example has even more jargon.
Atmospheric water, efficient process for capturing and delivering water, design and
demonstration, metal organic frame work, of course, ambient conditions.
Low-grade heat, a flux of less than 1 sun,
relative humidity levels, no additional input, all of that is scientist speak.
I should point out that if your writing for general American audiences....
The metric system is also jargonned to american audiences, so
you have to translate into English units as I've done here.
Just to give you an example from one of my Stanford students,
he was writing an article on prions and this was a paragraph from his first draft.
And so he had words like gain of function protein, aberrant process.
Confined to the space of disease.
Natural confirmation changes stochastically are induced by.
Of course, all of this is jargon to a lay person.
But it took me pointing it out to him, for him to even recognize it as jargon.
The third thing you have to do is to unpack the science.
When you write for a scientific audience.
You can be lazy.
You can assume a basal amount of scientific knowledge.
For example, you can assume that your reader knows how a gene works, or
how receptor ligand binding works, or what a T test is.
With general audiences, you cannot assume any prior scientific knowledge.
You have to explain the science from step one, and this is hard.
To be able to explain the science step by step to others,
you have to deeply understand the science yourself.
In the one on water harvesting, the scientists described the device in
a way that assumes prior scientific knowledge.
When I read their description, I didn't really understand how the device works,
because I didn't know what's a metal organic framework, and
I didn't know where the solar energy was coming into the system.
I actually had to go to YouTube and
watch videos to educate myself on what's a metal organic framework.
After some research I came up with this description.
The new device contains a porous crystal (called a metal-organic framework)
that soaks up water vapor like a sponge; a small solar panel provides the energy
needed to condense the water into liquid.
A few years ago, I was writing a magazine article where the crux of the story was
the trade offs between digital and analog systems.
So for that story,
I had to explain to lay readers the difference between digital and analog.
That's a concept I take for granted.
I teach statistics, so to me, the difference is
just the difference between continuous variables and discrete variables.
But I knew I couldn't explain it to a lay audience this way.
I had to rack my brain to come up with a good explanation.
I had to think really carefully about, what is digital?
What is analog?
What are the trade offs?
I finally came up with an analogy about how you would add graded
lighting to a room.
The analog solution would be to add a dimmer switch.
The equivalent digital solution would be to put, say,
ten light bulbs on the wall, each with it's own on/off switch.
This would allow you to precisely control the lighting in the room, but
there's a cost.
The digital solution takes much more energy, time, space and parts.
It took me a while to come up with that analogy.
One of my Stanford students was writing a piece about the brain, and
in her first draft she used the term neural projection.
So I wrote a comment back to her and said, what's a neural projection?
Is that an axon, is that a bundle of axons?
Is that something other than an axon?
I had never heard the term before.
And we, actually, went back and forth on several drafts and
I kept asking, what's a neural projection?
And then, finally, I think it was about the third draft, she wrote back to me and
she said actually, I don't know what a neural projection is.
That's just the term the scientist used.
And I was like, aha, that's the problem.
If you don't know what it is, there's no way you can explain it to others.
So I made her go back to the scientist and figure out what it is.
It was just his fancy way of saying axon, in the end.
One of the most critical skills, I think, in writing for
general audiences, is the ability to prioritize details.
When you write for
a journal article, you have to include all the nitty-gritty scientific details.
What strain of mice did you use?
What company did you buy the chemicals from?
What statistical test did you use?
But when you write for general audiences,
you have to filter some of these lower level scientific details out,
they're just not meaningful or relevant for a lay audience.
Many people have a misconception that writing for a lay audience involves
somehow dumbing down the science, and I completely disagree with this view.
I think what you're doing, when you write for
a lay audience, is that you're filtering out the less important details, and
you can do that without sacrificing accuracy.
Good science understand and vet the lower level details, and then make
a conscious decision about which details to prioritize and which to filter out.
I think of scientific knowledge as involving multiple layers of detail.
At the top, is the big picture.
Say, if you're doing a drug trial of weight loss,
it might be that the drug treatment beat the placebo.
The next layer, includes details that are critical to
evaluating the quality of the study, such as how many people were studied.
And how long they were followed, and how big was the weight loss in both groups?
The next layer includes details that would be meaningful to a lay audience, but
might be omitted from a very short story on the trial.
Such as, were participants and investigators blinded?
And maybe the dosing of the drug.
The next layer, might contain some technical details,
such as the randomization scheme and what statistical tests were used.
Below that might be some more trivial details,
such as what brand of weighing scale was used to weigh the participants.
A scientific audience needs all these details, so
that they can evaluate the quality of the study and potentially replicate it.
A lay audience simply doesn't need all these details.
Depending on the length of your article, l might stop two layers in, if it's
a very short article, or l might go down to three layers for a longer article.
The rest of the details, I'm going to filter out.
In the one about physical activity,
the authors gave three different numbers to convey the size of this study.
But you don't want to bombard a lay reader with too many numbers, so
I prioritized the number of countries and the number of people.
I thought the least meaningful number here, for a lay audience,
was the total days of physical activity, so I filtered that out.
For the water harvesting study, the authors start with this interesting tidbit
about exactly how much water is available in the air, on earth.
Now, that's an interesting detail, and
in a longer piece I might put that detail in later on in the piece.
But for a short piece, it's not an essential detail, so
I'm going to filter it out.
A lay reader doesn't need to know the exact level of humidity at 20%.
Mostly readers don't think in humidity levels, too often.
So if you just say dry or desert air, that's more meaningful to them.
Obviously, a lay reader doesn't need to know the chemical formula of the metal
organic framework.
And most readers aren't going to be familiar with units of sun, so
you can also filter that out.
The fifth scale, is that you need to get to the point faster.
When we write journal articles in science,
we tend to take our time getting to the point.
We start with why something was done, and then we say what was done, and
then what was found, and then what it all means.
A lay reader is not going to bear with you if you take that long to get to the point.
You have to cut to the chase.
And doing that, involves trusting your reader.
Your reader may not know a lot of science, but
you have to assume that they're intelligent and can make inferences.
For example, if you say what a study found, implied in that,
may be what was done and what it means.
So you don't have to spell out all three of those things for your reader.
Don't hold the reader by the hand and provide them with a running commentary.
Trust your reader to be able to make small leaps.
In the physical activity example,
the authors started with two sentences about the study design.
The first sentence gives a general description of the study.
The second sentence gives a specific description of the data set.
A lay reader doesn't want to sit through both of these so I just went straight for
the specific description.
I said researchers use data from smartphones to look at the walking habits
of the 717,000 people from 111 countries.
Cut the chase, right to the point.
One of my Stanford students was writing a story about this experiment they did in
mice where they rewired the connections between the taste buds and the brain.
So that sweet taste buds were perceived by the brain as bitter, and
bitter taste buds were perceived by the brain as sweet.
She'd already explained all of that and then she got to explaining the experiment
where they verified that the rewiring had actually worked.
And in explaining that, she goes through why it was done.
She says, in order to examine if this rewiring led to changes in behavior.
Then she says what was done.
Researchers observed the mice as they tasted these different tastes.
She says what it all means.
The mice who were altered seemed to have more of a tolerance for bitter taste.
And then finally she says what was found.
The altered mice licked the quinine more than the unaltered mice.
In fact, we don't need to go through all of that.
In my edit, I edited this down to just one sentence.
I just said what was found.
The mice with the altered bitter taste buds licked quinine, a bitter substance,
more than unaltered mice.
And notice that implied in that is the why the scientist did it,
the what they did, and the what it all means.
You don't need to spell it all out for your reader, just get to the point and
get there fast.
Finally, to appeal to wide audiences, you have to tell a story.
People don't connect to abstract ideas.
They connect with stories.
So in your lab you may be working on a particular gene or molecule or
chemical reaction or device that you find to be fascinating.
You're immersed in that science every day so it seems inherently exciting to you.
I hate to tell you though, if you go outside of your lab and try to explain
that molecule or gene to somebody outside of your lab they're probably not going to
find it all that interesting, especially if you explain it as an abstraction.
If you want to engage people in your science
you have to tell the science as a story, something people can connect to.
And what's a story?
A story has description, it appeals to the five senses,
it has plot, a drama and suspense.
It has characters.
Remember scientists are human beings, after all, they're characters.
Now, in those short lay summaries I showed you earlier there wasn't a lot of room to
use storytelling techniques.
You could think of those as short little stories.
But to be able to illustrate some story telling techniques I'm going to show you
a larger magazine piece that I wrote a few years back.
In this story I was actually assigned to write about a specific research study
that had just been published in Science magazine.
And it was on plant biology, and to be very honest, I didn't expect it to be
all that exciting to me because I've never been that interested in plant biology.
But this turned out to be one of my favorite stories ever
because the researcher, Professor Virginia Walbot of Standford,
turned out to be this amazing, fascinating woman.
And for example, she invited me to interview her at her outdoor laboratory.
So there is this corn field in the middle Stanford campus that l didn't know about.
And l met her there at 6 AM in the morning and was just as beautiful,
peaceful outdoor laboratory.
And as we were standing there talking all of the sudden the corn stocks
became blanketed with birds.
And l looked at Dr Walbot and said, what just happened?
So she explained to me that as soon as the temperature hits a certain level,these
little bugs called aphids come out and those draw out the ladybugs and
those draw out the birds.
But it was just this amazing moment.
And so I used all of that as the opener for my piece to draw my reader in.
And then Dr. Walbot was a pioneer for women in science.
And she had some amazing stories about being an early woman in science.
And so my editor and I decided to actually expand the piece to be
about more than just her recent research article, but
also about her experiences as an early woman in science.
One of the stories she told is, she did her doctorate at Yale in the late 1960s.
And on the first day her department head got up and he was all proud and
happy because half of the incoming class were women.
But he says the reason he was proud and happy is that there is no better
combination than a male professor with a PhD wife to run his lab.
And that tells you a lot about the state of women in science at that time.
But by couching the science, by putting that research in the context
of her laboratory and these stories and her experiences,
that made the science more interesting and more accessible for general audiences.
So you have to be a story teller.
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