Biomedical pyramid, de-structuring


How We’re Unintentionally Defunding the National Institutes of Health, by Michael White



Paula Stephan, an economist at Georgia State University, argues that many of the research community’s problems flow from two big features of how we do research. First, we staff our labs with low-wage, temporary workers—graduate students and postdoctoral fellows who move on after a few years. This means that universities have an incentive to recruit and train more students and postdocs, regardless of their eventual job prospects. The result is unsustainable. As Stephan writes, “the research enterprise itself resembles a pyramid scheme.”

The second structural problem is that career rewards in science are doled out according to a “tournament model,” a situation in which small advantages—in productivity, skill, or network connections—translate into large differences in rewards like faculty jobs, grant funding, and tenure. Tournament models foster intense competition, but they can be incredibly wasteful: the differences between a proposal that is funded and one that is not can be small and arbitrary. These small and arbitrary differences are making and breaking scientific careers in which taxpayers have invested substantial resources.


Paula Stephan, The Biomedical Workforce in the US: An Example of Positive Feedbacks,

“…with rigor and careful analysis…”

Drawn out of my deep blogging slumber by PZ Myers’s magnificent slam of bad evolutionary psychology (leaving the question of good evolutionary psychology open, since this is all about “…rigor and careful analysis…”).  It’s a long post that criticizes arguments made by Jerry Coyne (who weirdly enlisted Steven Pinker to do the heavy lifting) and worth reading for more than the few excerpts I pull out here.

My favorite part, responding to a particularly lame rhetorical move made by Coyne:

Please. Have I ever said that we shouldn’t study gender or racial differences? No. We know there are going to be differences. The catch is that they have to be studied very, very well, with rigor and careful analysis, because they are socially loaded and because science has a deeply deplorable history of using poor methods to reach bad conclusions that are used as ideological props for the status quo. I’m not putting up roadblocks against scientific research; I would like to put up roadblocks to sloppy, lazy ideological nonsense touted as scientific research. I should think every scientist would want that.

What I am most taken by is the phrase I quoted for my title, “with rigor and careful analysis.”  You could just read this as redundancy, repetition to make a point about why scientists can’t be “sloppy” or “lazy” (it may be that they can be “ideological,” so long as they are  careful and vigorous enough to be sensibly so, but that’s an argument for another day and I have to confess that “ideology” is not a subject I care to get into in general). But you could also read it in a way so that they appear to be two different things; “rigor” alone, then, is not enough for doing science well, but you also have to add this other thing called “careful analysis.” Going out on a limb farther than I probably should: Coyne and Pinker don’t lack for rigor, but it’s PZ Myers who comes off as the really careful one here…

(Comment threads at both places are extensive.  If I were forced to pick between which comment thread community to join, were I to ever do something like join a comment thread, the one at Pharyngula would win hands down.  Somebody named Jason gamely tries to take on some of the more stridently scientistic commenters with some references to Spivak, but there’s not much traction to be gained here.  For all my talk about ‘friendship with the sciences” and the importance of dialogue, this is a good reminder that some of them sure don’t make it easy.)



Science and the Difference Between “Oh!” and “O!”

Evolutionary theorist and poet Jon Wilkins takes evolutionary theorist and non-poet E.O. Wilson to task for his recent opinionating about why math is not a requirement for being a scientist.  Like Wilkins, I’m not particularly interested in that debate, which I think is pretty much a non-starter. Wilkins steers us more to matters of collaboration than math, which he likens to matters of translation in poetry.  He relates a story told by Robert Haas, who has translated seven volumes of poetry by Czeslaw Milosz from Czech to English.  Haas was translating one of Milosz’s last poems — or, as Wilkins prefers to put it, “more accurately,” Haas “collaborated with Milosz” on the English version of the poem, which Milsoz had titled “Oh!”  Haas wrote to him to ask if he meant “Oh!” or “O!”  The Nobel laureate asked Haas

what the difference was and said that perhaps we should talk on the phone. On the phone I explained that “Oh!” was a long breath of wonder, that the equivalent was, possibly, “Wow!” and that “O!” was a caught breath of surprise, more like “Huh!” and he said, after a pause, “O! for sure.”

Wilkins writes:

Poetry is about subtle differences in meaning. It is about connotation and cultural resonance. It is about the sounds that words make and the emotional responses that they trigger in someone who has encountered that word thousands of times before, in a wide variety of contexts.

These things almost never have simple one-to-one correspondences from one language to another. That means that a good translation of poetry requires a back-and-forth process. If you have a translator who is truly fluent in both languages — linguistically and culturally — this back-and-forth can happen within the brain of the translator. But, if your translation involves two people, who each bring their expertise from one side of the translation, they have to get on the phone every so often to discuss things like the difference between “O!” and “Oh!”

Doing mathematical or theoretical biology is exactly like this.