"I Don't Know If I'm a Scientist": The Problem with Archetypes

Scientific American
"I Don't Know If I'm a Scientist": The Problem with Archetypes

View photo

"I Don't Know If I'm a Scientist": The Problem with Archetypes
I, like all young researchers starting our toils in science, sit at an interesting juncture. We have a portal to the past lives of scientists through our mentors and texts: we know some of how things were done and by whom. At the same time, as the children of this world we have our ears closer to the ground, instinctively aware of the current state of the scientific community, its interactions with the rest of the world, and what's to come.

One change I find occurring is a shift--stemming from where I'm not sure--in the cultural caricature of a scientist. It is a shift away from an arguably negative and nerdy portrayal towards a more socially favorable one (a change that is understandably welcomed by the older generation of scientists who struggled against stereotypes involving pocket protectors and poor social skills). But inasmuch as society's view of scientists remains a mere caricature, it stands in the way of a fuller acceptance of what 'scientist' can mean.

Under the new view, scientists are no longer detail-obsessed and emotionless observers, concerned only with accuracy and precision. Instead, the likes of Neil DeGrasse Tyson present the scientist as an energetic and passionate explorer of the universe--one who seeks to boldly know what no one has known before. We, as scientists, are meant to proudly and openly exclaim our love of all knowledge for knowledge's sake. As kids we tinkered and took apart our toys just to see how they worked. And as adults we continue to ceaselessly manipulate the world around us in an attempt to quench our curiosity about it. Smarts are still necessary for a scientist, but now we must be equal parts calculator and cowboy.

The transition from scientist as stoic, number-muttering and bespectacled introvert to a quirky, curiosity-fueled investigator (still bespectacled perhaps, but only as a stylistic choice) is objectively a positive one. And in acknowledging the emotional drives involved in pursuing science, it is a more well-rounded portrayal as well. But to me there is still a tension. The persona of a swashbuckling scientist doesn't fit me, or many of my peers, any better than the socially-awkward geek did. Hearing either description makes me wonder, even as I work towards a PhD in Neuroscience, am I scientist?

The problem is that, when replacing one stereotype with another, a stereotype is still what we're left with. Allowing for the definition of 'scientist' to include passion and energy is helpful, yes, but the problem really stems from trying to define 'scientist' in the first place. 'Describe the average scientist' is about as reasonable a request as 'describe the average color'. Our population is too vast, too diverse, too ill-defined, and too non-overlapping to be characterized properly by some kind of Platonic form. An arrival at a scientific career can be preceded by unknowably many paths, and the style and skills employed once there are equally diverse. One needn't have tinkered as a kid to do science as an adult, and the science one does may involve everything from trekking through wildlife collecting samples to sitting at a computer writing code.

Furthermore, the notion that all scientists share a universal and unbounded curiosity about all the workings of the world can easily be disproved in this age of intense specialization. I've met an entomologist driven by aesthetic appreciation of caterpillars to learn every detail of their lifespan and speciation, but I doubt she would give much attention to my thoughts on the role of the hippocampus in memory encoding. There are physicists who see little excitement in anything larger than an atom, and translational biologists who consider finding disease treatments the only worthwhile task.

Even within the neuroscience community, theorists who are intensely passionate about discovering what computations our neural circuits are carrying out possess only a passing interest in the molecular details of how they're doing it. Certainly there are still some polymaths sprinkled across the scientific community--modern-day "naturalists" with a genuine interest in how the world functions on all levels. But for many of us, the only trait we have in common is a belief in the exclusive importance of our own line of research.

Rather than attempting to present a unified vision of what a scientist is, the scientific community and the public would be better served by embracing the diversity and complexity that is the truth of the scientific population. The notion that there are some qualities, some 'spark' required to be in science creates a false sense of a divide between scientists and non-scientists and runs counter to the intention of encouraging more people to take interest in the subject.

The only requisite to be a scientist is to participate in the scientific process. Science doesn't need to put forth a mascot as a recruiting tool: the content of our work should speak for itself. Let a fascination with the night sky lead a child to become an astrophysicist. Or let concern for the environment catalyze a change of careers for an adult. To convince people to get involved should require only an accurate presentation of the substance of the science itself and a clear message that science is open to everyone. The best way to truly impress upon people the idea that anyone can be a scientist is to not offer any definition of a scientist at all.

This piece was drafted during the Communicating Science 2013 workshop (ComSciCon), sponsored by Harvard University, MIT, and the Microsoft Corporation.

Image: Neill DeGrasse Tyson image is in the public domain, obtained from http://www.blackpast.org/?q=aah/tyson-neil-de-grasse-1958

Follow Scientific American on Twitter @SciAm and @SciamBlogs.

Visit ScientificAmerican.com for the latest in science, health and technology news.

© 2013 ScientificAmerican.com. All rights reserved.

View Comments (7)