The other day, Nicholas Christakis wrote an article in the newspaper criticizing academic social science departments:

The social sciences have stagnated. . . . This is not only boring but also counterproductive, constraining engagement with the scientific cutting edge and stifling the creation of new and useful knowledge. . . . I’m not suggesting that social scientists stop teaching and investigating classic topics like monopoly power, racial profiling and health inequality. But everyone knows that monopoly power is bad for markets, that people are racially biased and that illness is unequally distributed by social class. There are diminishing returns from the continuing study of many such topics. And repeatedly observing these phenomena does not help us fix them.

I disagreed, saying that Christakis wasn’t giving social science research enough credit:

I’m no economist so I can let others discuss the bit about “monopoly power is bad for markets.” I assume that the study by economists of monopoly power is a bit more sophisticated than that! I have studied racial profiling, and I can assure you that this work is not about the claim “that people are racially biased.” Regarding the question of illness being distributed by social class: Is it really true that “everybody knows,” for example, that Finland has higher suicide rates than Sweden, or that foreign-born Latinos have lower rates of psychiatric disorders? As Duncan Watts has written so memorably, it’s easy to say that everything is obvious (once you know the answer).

Christakis responded in an email and in a comment:

I admire and respect your work, and so I am surprised by the tone of some of your comments on your blog.

Have you had a chance to read any of our papers recently? We have many experiments and observational studies in major journals that have survived grueling peer review. We have also responded at length to our critics. Here is the recent response to our critics (with comments and rejoinders):

http://humannaturelab.net/wp-content/themes/human-nature-lab/media/pdf/publications/articles/SIM_special.pdf

And here are a few papers (from Nature and PNAS) that further explore social networks using diverse methods, both observational and experimental.

http://humannaturelab.net/wp-content/themes/human-nature-lab/media/pdf/publications/articles/127.pdf
http://humannaturelab.net/wp-content/themes/human-nature-lab/media/pdf/publications/articles/126.pdf
http://humannaturelab.net/wp-content/themes/human-nature-lab/media/pdf/publications/articles/106.pdf
http://fowler.ucsd.edu/massive_turnout.pdf

One cannot have it all, Andrew, as you know very well. If we use observational data, nihilists (who you often take on!), criticize the difficulty (in the limit, the impossibility) of causal inference; if we use experiments, critics object to the lack of verisimilitude.

Finally, as someone who spends a lot of time trying to advance the public understanding of science (I mean you, not me!), i don’t think you really should be calling the kettle black.

As to your original complaint, let me say this: my main point (within a constrained 800-word format, for which the editors write the title, not the authors) is that we can learn something from the natural sciences about institutional forms and about ways of doing science (just as they surely can learn from us). This does not mean what we social scientists are doing is bad; but it would be arrogance to assume we have nothing to learn. And re-deploying talent to tackle new (and, yes, old!) topics is fine, but we should be judicious, and, yes, I think we should move to the scientific frontier. Is that a claim you don’t agree with?

My response:

I agree with everything above. What I didn’t agree with in the op-ed was the emphasis on diminishing returns from the continuing study of topics such as monopoly power, racial profiling, and health inequality. I think this stuff is on the scientific frontier too! One source of my strong reaction here could be from my time at Berkeley, when my colleagues in the statistics department were mostly split into three groups: (1) those who did pure mathematics and had no interest in my work, (2) those who felt that Bayesian statistics was low-tech and thus beneath their notice (these people liked to “prove theorems” rather than “make assumptions,” not realizing that a theorem, to be applied, needs assumptions), and (3) those who did applied work in biology and felt that social science was not real science.

And I don’t want people to feel I’ve condemned Christakis and Fowler’s work. Over the years, I’ve pointed to criticisms of their research but I’ve also emphasized that these are difficult problems and that, as the very least, that work is an important first step using information that is available. I just don’t think this sort of work should be privileged over work on topics like monopoly power, racial profiling, and health inequality.

P.S. Also I’d just like to say that I really appreciate that Christakis commented at all. He could easily stayed above the fray and not responded at all, based on the quite reasonable theory that many more people would read his NYT op-ed than would ever see this blog. He could’ve been like Gregg Easterbrook and simply refused to ever acknowledge my existence, let alone my specific comments on his writings. I think it’s great that Christakis stands by his work and welcomes criticism.

P.P.S. Here’s the blurb I wrote for Christakis and Fowler’s book a few years ago:

Margaret Thatcher said there is no such thing as society. Hillary Clinton wrote that it takes a village. In their new book, Christakis and Fowler write, “We don’t live in groups, we live in networks,” and they back this up with dozens of interconnected stories of research findings by themselves and others, ranging from bank runs to suicide prevention, from nut allergies among schoolchildren to epidemics in virtual worlds, from the spread of happiness to the spread of voting. The combination of speculation and science is fascinating and leaves me eager to learn about the next wave of research in this area.

P.P.P.S. To move beyond a pointless who-misunderstood-whom back-and-forth, let me now shift the discussion to an interesting issue raised by Christakis:

What are the (relatively) settled matters in the social sciences? Can we social scientists can ever say that “we have pretty much figured this out” (as in the way biologists have figured out certain topics)?

I dunno. Krugman would say it’s settled that it’s a good idea to expand government hiring during a depression, but others disagree! For an example from psychology, stereotype threat is claimed by some to be very well established, while others have difficulty finding it at all. In various ares of social research, there’s debate about the replicability of all sorts of claimed effects.

Ideally, I think, once something is settled, this can be the staging point for more research. For example, Kahneman and Tversky demonstrated “anchoring and adjustment” and other so-called heuristics and biases. Then later researchers followed up with studies trying to crack open anchoring-and-adjustment, to understand experimentally how it happens and how to alter it.

Overall, I’d say that, if anything, social scientists perhaps don’t spend enough time re-confirming the definitive statements. There’s a real push toward novelty, to the extent that maybe we don’t have enough “gold standards” of well-established social patterns.