Forum:What is meant by referring to research studies as "stories"?

Question

[mcsimenc]

In the field of genome researchers, I have noticed that it is popular to refer to one's and other people's studies as "the XXX story"; "our ATPase story", for instance. Scientific reports are certainly different from stories in the common sense, which center on characters (people), their interactions, and development, and essentially comprise a beginning, middle, and end. Contrasted with this, these scientific studies are like explanations and hypotheses of mechanisms, informed by observations. I am not really sure how to reconcile these. What are your thoughts about this? If you refer to genome studies as stories, what exactly do you mean by it?

[ATpoint]

A "story" is the flow of the writing. The "narrative". Not the findings itself. Papers are rarely chronological, figures and data are arranged to make logical sense, to have some connectivity and to have an overall ommon thread. Some figures are eye candy or supportive but dispensable while visually attractive, others are of critical importance. Lots of the paper content is "selling" the "story" rather than being 100% scientifically needed. Sometimes maybe 25% of figures are critically important, but few decent journals accept a super-few-figure paper. Publication is not entirely (or at all?) about the science alone.

Answer 1

[Ram]

A story explores one or more core messages and lays out the author's perspective/narrative. A study explores one or more hypotheses and lays out the author's (researcher's) observations/analyses. That's the parallel I see.

You are looking at the surface level components of a story. If you need those parallels, look (for example) at genes as characters, their interactions and products. An initiation, a reaction/pipeline and an end result. Much like the structure you laid out.

Answer 2

[Philipp Bayer]

Here's my take: every dataset you look at contains infinite stories. Which story you end up telling depends on your interests, your background, your research environment etc.

For example, if you give me 50 plant genome assemblies, I'll look for NLR genes and their diversity, dig a bit into loss and variability of these genes, and write up what I'll find, pretend I had a hypothesis in the first place (see Medawar's Is the Scientific Paper a Fraud?), write up results and discussion. That would be a NLR-focused story, that's where a lot of my track record lies, that's the first idea that would come to my mind, and where I can use my previously learned skills.
Somebody else will look for Restorer-of-fertility genes and tell a story around those genes because that's where they are coming from.

Yes it'll be a hypothesis focused on information, but every dataset, every experiment contains different stories you can tell.