How Do You Do Science?

"You put up a candidate and then try to tear it down. And, if you can't tear it down, it's probably bona fide. That's how we do science."

Bees are dying off to an unusual degree. Although one researcher has found that there were 14 die-offs in the past 100 years, the current die-off so far seems more confusing and less explicable. So we find that Colony Collapse Disorder (C.C.D.) has been all over the news this year. So much so that now if we say "Bees" and "CCD," many readers will have some recognition. We offered a brief post on the issue a few months ago, noticing then the astonishing range of contact bees have with so much of our food supply. Thus, if the bees go, that's really bad news for us and for our food. Ergo, in an anthropocentric way, we need to pay attention to this. Of course we need and should not reduce the issue to that, but it's a common one.

Two new bee stories came across our desk this past week, one from Adbusters, of all places, the other in The New Yorker. The Adbusters article, by Eric Rumble (Aug. - Sept. 2007, #73), is called "Monotech: What agribusiness has done to the honeybee." It discusses "how industrial agriculture and commercial beekeeping have created larger bees in the pursuit of more honey and of course more money. The larger bees are more vulnerable to disease and infections." The New Yorker article discusses how scientists are pursuing more technical explanations, but not much about urbanization, industrial practices, commercial motivations, mono-crop proclivities, etc. So, the range of suggested "causes" of the problem include (to quote Rumble) "The encroachment of urbanization, toxicity from pesticides and genetically modified crops, tracheal and Varroa mite infestations, Nosema ceranae and other fungi, African honeybee genes, bacteria from small hive beetles, poor nutrition from fructose-spiked corn syrup, stress from unprecedented migration, immune deficiencies and - as widely misreported - cell phone radiation." But this post isn't about causes. It's about explanations.

What struck us as most intriguing was the commentary on how the disorder had become defined and now had it was being put to the test. The trial, the court, the proof, the verdict - these legal terms are all embedded in scientific practice. In Science and Technology Studies, and often from what's called Actor-Network Theory, the concept of "trials of strength" has been influential in how we understand how science works. (Bruno Latour's work in particular defines this -- see (1987) Science in Action for starters.) Other scholars have traced the long built connection between legal practices and metaphors and scientific ones, going back to Francis Bacon (a lawyer), his conception of a scientific house of inquiry, and the early modern period in the history of science. Yet others devote a good deal of necessary attention to the continuing cross-over between the courtroom and the laboratory - in direct terms, as in with evidence and testimony; in conceptual terms, as with the relationship between proving that evidence is valid to a jury of peers (a peer review); and in the related credibility and persuasion terms, as in showing what it takes to make your case to those peers, and what styles of argument and persuasion one uses to do so.

So the explanation in Kolbert's article by Ian Lipkin, who is the head of the Jerome L and Dawn Greene Infectious Disease Laboratory at Columbia University's Mailman School of Public Health, was particularly fascinating. To repeat: "You put up a candidate and then try to tear it down. And, if you can't tear it down, it's probably bona fide. That's how we do science."

One virtue of the scienceblogs readership is that we get a wide range of kinds of readers - PhDs, graduate students, undergrads, practicing scientists and engineers and technicians and associated laboratory workers, science enthusiasts, even apparently high school kids and younger. I thus put the question to that range of readers:

How do you think "we do science"? And what do you make of the "trials of strength" model?