Recently I was discussing my dissertation progress with another volunteer at the bird banding station. “I have all the data,” I said, “I just need to figure out how to spin it.”
She looked taken aback. “Well, it’s data,” she said. “It’s information. You don’t spin it; it just is.”
“Right,” I agreed quickly, in my best Objective Scientist voice. “Of course.”
I thought about this exchange a lot over the next few weeks. It had been a while since I had talked about my research at length with a non-scientist, and her reaction to my word choice made an impression. Why had I said “spin”? Did I mean “spin”?
I paid more attention than usual to the word choices my colleagues made, and quickly realized that we all talk about spinning our data. We also talk about interpreting our data, and framing our data: similar and related concepts, but not exact synonyms for spinning the data. “Spinning” sounds underhanded, deceitful. It sounds like we are making the data say what we want it to say. Shouldn’t the data speak for itself?
Data is information, yes; but it usually doesn’t speak for itself. Data needs help to speak. A good graph can show anyone who looks at it some conclusion—but someone had to make that graph first, make decisions about its design that affect what conclusion, what story, a viewer will see. And a lot of the sorts of data we get in ecology and evolution research need some background and interpretation to tell any story.
Imagine, for example, a study on the relationships of different species of turtles.
This seems pretty straightforward: the results will be a diagram of the species relationships. Simple. But one could tell a number of different stories about it: one might be, “Turtles are related the way we would have predicted based on their shell shapes.” Or, “Turtles have evolved pointy heads multiple separate times: pointy heads must be important.” Or, “Turtles are so closely related that we need new genomics methods to really tell how they are related, because the current methods aren’t working well.” Or, “The Brontosaurus-necked Turtle should be in its own genus.”
These are all objective conclusions one could make from data; but they require a good background knowledge, and an idea about what to do with the data. More, they change how a viewer looks at the data: they tell what to look for, what patterns to evaluate.
In my own research, I’ve struggled with this most with one particular result. In general terms, I found that the juncos do not do what I was pretty certain they would do. When I tell people about it, I’ve tended to say: “I thought they would do [thing], but they don’t.” This is an accurate presentation of my data, but not a very informative story. Better would be: “Juncos elsewhere do [thing], but the ones I studied don’t, probably because of [reason].” Or even, “I discovered that juncos pursue [strategy], so that some do [thing] while mine do [alternative thing].”
When scientists say we are spinning our data, we mean this: telling a story about the data. We mean interpreting the data and framing it with relevant background, and presenting it as a whole concept to an audience. I think we like to pretend, sometimes, that we simply collect data and pass it on to the public as pure results (well, or to each other, at least; I’m aware that the public probably doesn’t make a habit of reading, say, Behavioral Ecology and Sociobiology). But that leaves out an important part of being a scientist. We don’t just email each other Excel spreadsheets full of data when we finish a project; we write papers with sections titled “Introduction” and “Discussion.”
The reason that becoming a good scientist takes a lot of time, and studying, and trial-and-error, is that it isn’t as simple as collecting the data (which certainly isn’t simple either): you have to know what story to tell with that data. Turning the data into a story—spinning it—isn’t deceitful: it’s how you explain to everyone else what you found.
well said. no matter the topic every narrative is influenced by the writer
I loved this post! Very well written… and your very last sentence says it all! :)
This is a really good post on something which affects us all as scientists. Humans love a story, and if we don’t spin a good narrative from our data it has no impact. If it has no impact you don’t get funded.
But this is where the ethics come in. The story has to be true. More than that, to be scientific, the alternative, more mundane truths should be presented. Also all data must be made available for others to judge.
In my field, maybe unlike yours, multi billion dollar industry dominates the literature. The temptation to spin is enormous. Some leading papers are written by professional writers employed by the sponsor, and I am not sure how much the lead academic authors scrutinise the data. We do work in a highly regulated environment, by the way, to ensure complete and unbiased data collection, but still … It’s how you spin the data.
Ben Goldacre’s Bad Science, and later, Bad Pharma, are great texts on this. When we discuss about how to present our data to maximise impact, we sometimes cite him as showing what not to do. I’m reading a pop text called Phishing for Phools, which shows how our hunger for narrative is widely exploited, and is largely the foundation of the lucrative pseudoscience of Economics.
“…to be scientific, the alternative, more mundane truths should be presented.”
A critical point! Even once you have a good, true story, the alternatives must be made available for comparison. Any paper that doesn’t have alternative interpretations mentioned immediately sends up red flags. (This is a challenge for me in writing, as I tend to err on the side of doing too much of this, resulting in Discussions that are over-long, exhaustive lists of alternative explanations. I’m still working out how to acknowledge the alternatives while not giving them more attention than they need.)
Thanks for talking about your own field – I confess to some relief at being where I am :-) There are always incentives to spin in a particular direction, which is where one’s scientific ethics come into play. Nothing makes it easier to get research funding, whether from biomedical companies or non-profit funding sources, than getting “good” results.
It’s interesting how different groups within culture use the same words with such different meanings. In media relations, when someone spins a story they are leaving the truth behind to tell their torqued version of events for their own benefit. From what you say, scientists use the word spin to mean a true story. To be honest, I had never encountered a situation where spin is a positive term until this post so I learned something. I wonder why scientists chose the word spin?
To make matters even more interesting I have encountered some people who interpret the word story as something that is not true. That makes it even more complicated to communicate what you want.
Exactly – in some circles, “spin” WOULD be a synonym for “lie.” As I was working on this post, I looked up the official definition of “spin,” and got: “a certain way of describing or talking about something that is meant to influence other people’s opinion of it” (Merriam-Webster). Which at first sounds like the deceitful version, but after some reflection… you hardly ever talk about something without having some idea what you want people to take away from your words. And we’re back to this ambiguous concept that can mean one thing to one group of people, and a different thing to another. As to why we use that word in the first place – I don’t know. I’m sure I adopted it after hearing it used by the scientists around me, and it is a useful concept for us, but I don’t know who first used it in this particular context.
The issue of “story” implying fiction wasn’t one that had occurred to me; thanks for mentioning it. I certainly don’t mean it that way!
I, too, was surprised to hear “spin” used to mean framing or story-telling, because I associate it with political biases. If you say you’re uncertain about how to spin something, it means you really are being objective: the spin wasn’t already there, influencing your data. I associate story-telling with good communication and interpretation; I associate “spin” with misleading someone, or making data seem more dramatic than it is (like those graphs that start at 30% and go to 35% but are set up to look as if they go from 0% to 100%).