Improving Interpretation of Science Writing

Stories of recent fraudulent science seem uncomfortably common. In many of those cases the scientists are blamed, and rightly so. Sometimes criticisms identify more systemic problems like current scientific practice, or scientific institutions like the NSF or a university, or academia in general. Blame is also often laid on pop science and the popular science writers who try to tell a counterintuitive and interesting story, or who are under pressure to write frequently and under a deadline.

Research at Disney

If the talk about a shortage of faculty positions is dispiriting, articles like this are energizing. Data science has emerged as a hopeful and interesting alternative to academic social science. But one of the biggest drawbacks has to be that many data science positions are shaped so exclusively by computer science, engineering, or some other area of science that isn’t primarily social. Those areas of work are great, integral and critical, but the result of the skew is that descriptions of “data science” can lose sight of the real human behavior and social phenomena behind the data being analyzed.

What happens in society, stays in …the brain?

I finally had the chance to catch up on my reading this morning, and at the top of the list was this “We Aren’t the World” article. As Schaun pointed out in his last post, the basic narrative behind the piece (and a lot of the discussion around Henrich’s work) is that science is moving away from the view that humans have more or less universal cognitive faculties. This old view assumed everyone would respond similarly to basic stimuli. But then Henrich and others came along and showed that people respond differently to those stimuli. So now we know that cognition itself is shaped by “culture, environment, etc.”

Data science? Yes, please. Data scientist? Meh.

I wrote a post a while ago about not being sure if I wanted to call myself a data scientist. The post was less about what title I wanted to ascribe myself and more about the many divergent ways “data science” seems to be defined. At the time, I wrote:

Science is more than its methods (but social science currently isn’t)

Paul called my attention to this piece (behind a pay wall…of course), titled “The science in social science” and written by anthropologist H. Russell Bernard. When I was doing my graduate work at UCONN, we commonly referred to Bernard’s Research Methods in Anthropology as our “methods Bible,” so I went into his article with favorable expectations. Unfortunately, I think he engaged in some logical leaps that I just can’t make. From his abstract: