I will resist the temptation to jab a pencil into my forehead. Every time the phrase "big data" is uttered a data scientist sheds a tear. Or I contemplate a self-induced lobotomy. Our super-sized collective mentality is convinced that bigger is better. Not necessarily. High-quality evidence is often shoved out of the "limelight" as spurious claims are splashed across transmedia news outlets.
I was recently at the Science Writer's Bootcamp sponsored yearly by the Johns Hopkins Institute for Basic Biomedical Sciences. The topic this year was Weighty Matters: Recent Advances in Metabolism, Obesity and Diabetes Research.
The schedule allowed sufficient time for networking with attendees and presenters. I was somewhat shocked when the sole attendee from a singularly popular health news announced that he was just learning the science as he goes--but he was an experienced reporter so it was working out okay!?
My immediate concern about events targeted for science writers are data highlights presented in the absence of context. Sure you can show a graphic but what about the framework for the audience to determine if the claims are warranted.
A colleague mentioned quite astutely her concerns regarding the axes in one of the graphics (see below). "Hey did you see that scale on the graphic?" We conferred that the visualization would look different if presented correctly. It makes you wonder that the 10 to 11 week post-irradiation data might have shown in the male rats.
I know it seems like I keep repeating myself but what we really need is improved numeracy. Journalists and writers need to understand the data. The spurious associations and dubious claims are the purvey of anyone hoping to tell a hidden story. Not to be a "gotcha" fanatic but to keep the bar high--and rising.
brings up a good point but I am afraid not enough people are even looking--or concerned.
It reminds me of a saying by Seth Godin: