Certifiably reproducible science… meh

A movement is afoot to create formal structures to reproduce experiments (Ars Technica):

Almost nobody goes back and repeats something that’s already been published, though.

But maybe they should. At least that’s the thinking behind a new effort called the Reproducibility Initiative, a project hosted by the Science Exchange and supported by Nature, PLoS, and the Rockefeller University Press.

John Timmer goes on to write about reasons why some people think this is a waste of time. I agree with all of these reasons. Continue reading “Certifiably reproducible science… meh”

Pursue ignorance, learn science

Ignorance is not just a blank space on a person’s mental map. It has contours and coherence, and for all I know rules of operation as well. – Thomas Pynchon, Slow Learner

Dr. Stewart Firestein, a Columbia University neurobiologist is a scientist after my own heart. A former actor and theater manager, he went to graduate school in his mid-thirties, and despite the late start, has pursued a successful career understanding olfaction. He teaches a class on ignorance in science, and he’s written a book based on the ideas in the class, Ignorance: How It drives Science.

The basic message of the book is that facts are boring, while ignorance is (or can be) interesting, and we need to teach and practice science with this in mind. In this brief, genial book, Firestein gives advice on how to have an interesting conversation with a scientist – ask any of the following questions:

Continue reading “Pursue ignorance, learn science”

The state of R01 funding and how we got here

A snippet from Paula Stephan’s How Economics Shapes Sciencep. 141-143, Harvard University Press, 2012:

“The NIH Doubling: A Cautionary Tale”

It is tempting to assume that money is the answer to many of the problems that plague peer review and, more generally, the university research enterprise…

But anyone who thinks so should be careful what they wish for. The doubling of the NIH budget between 1998 and 2002 ushered in a host of problems…

Faculty were spending more time submitting and reviewing grants. Although early in this century 60 percent of all funded R01 proposals were awarded the first time they were submitted, by the end of the decade only 30 percent were awarded the first time… [T]here is little evidence that the increase translated into permanent jobs for new PhDs, as had been the case in the 1950’s and 1960’s when government support for research expanded. Continue reading “The state of R01 funding and how we got here”

Very old cave art shows how technology drives science

The exciting science news in this week’s issue of Science is that some cave art in Europe is much, much older than previously thought, dating back to the earliest humans in Europe. The new dates make it more plausible that some of this art was created by Neanderthals, although that is speculative.

While old cave art is cool, you may be wondering, why are they just now getting around to figuring out these old dates? The answer is, the technology finally got good enough to do it. The Uranium-thorium dating was done by scraping off a few milligrams of calcite deposits that had formed over the cave art. Since the calcite deposits formed on top of the art, dating those deposits gives you a minimum age for the art.

When Uranium Thorium dating was first invented, you needed tens of grams of sample, but the sensitivity of the technology has now improved 10,000-fold. You can take tens of grams of sample out of priceless cave art, but you can take a few milligrams.

And so, the new dates are not the result of some brilliant new, abstract, deep insight – they’re the result of amazing improvements in technology. Science is driven at least as much by technology as it is by ideas.

Even Boltzmann had trouble with probability

Boltzmann was one of the genius founders of statistical thermodynamics, and yet the subtleties of probability tripped him up:

From “Compendium of the foundations of classical statistical physics” by Jos Uffink:

He introduced the probability distribution as follows:

“Let (v)dv be the sum of all the instants of time during which the velocity of a disc in the course of a very long time lies between v and v + dv, and let N be the number of discs which on average are located in a unit surface area, then

N ϕ(v)dv

is the number of discs per unit surface whose velocities lie between v and v + dv” Continue reading “Even Boltzmann had trouble with probability”

%d bloggers like this: