Friday Sprog Blogging: more science fair brainstorming.

We continue discussions with the elder Free-Ride offspring about potential projects for the spring science fair.
Elder offspring: Maybe I could do an experiment with Mentos and soda.
Dr. Free-Ride: You mean that one where you use Mentos to create a fountain of soda?
Dr. Free-Ride’s better half: That’s not an experiment. It’s a cliché.
Dr. Free-Ride: Like sticking battery-leads into a dill pickle.
Dr. Free-Ride’s better half: But less illuminating.

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Argumentation: FAIL.

One of the big things philosopher-types like to do with their students is work on extracting arguments from a piece of text and reconstructing them. This can be useful in locating sources of disagreement, whether they be specific premises or inferences.
But some chunks of text that seem like they ought to have arguments that can be extracted and reconstructed end up being … opaque.
For example, this question and answer between Katie Couric and Sarah Palin (transcript by way of Shakesville):

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San Francisco millionth comment party this Friday night!

Just a quick reminder that the San Francisco party to celebrate one million comments on ScienceBlogs is tomorrow, Friday, September 26, starting at 9:00 PM at Tonic, 2360 Polk Street (at the corner of Union). I’ll be there, as will the brothers Bleiman, Craig McClain, Josh Rosenau, and Razib. If you show up, you’ll be there, too!
Also, don’t forget that until the end of September you can still enter the drawing for a fabulous trip to New York City, including a dinner with your favorite ScienceBlogger.

Gimme the money — hold the oversight.

From time to time on this blog, we discuss the obligation scientists assume by virtue of accepting public money to fund their research. These obligations may include sharing knowledge with the public (since public money helped make that knowledge). And they also include playing by the public’s rules as enshrined in various federal regulations concerning scientific research.
If a scientist takes public money, she expects there will be some public oversight. That’s just how it goes.
Of course, working from this mindset makes it much harder for me to fathom how someone (say a Secretary of the Treasury) could ask for a big chunk of public money (say $700 billion) with no oversight whatsoever. Indeed, in trying to make sense of such a request, I find myself entertaining some pretty odd hypotheses:

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How scientists see research ethics: ‘normal misbehavior’ (part 2).

In the last post, we started looking at the results of a 2006 study by Raymond De Vries, Melissa S. Anderson, and Brian C. Martinson [1] in which they deployed focus groups to find out what issues in research ethics scientists themselves find most difficult and worrisome. That post focused on two categories the scientists being studied identified as fraught with difficulty, the meaning of data and the rules of science. In this post, we’ll focus on the other two categories where scientists expressed concerns, life with colleagues and the pressures of production in science. We’ll also look for the take-home message from this study.

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How scientists see research ethics: ‘normal misbehavior’ (part 1).

In the U.S., the federal agencies that fund scientific research usually discuss scientific misconduct in terms of the big three of fabrication, falsification, and plagiarism (FFP). These three are the “high crimes” against science, so far over the line as to be shocking to one’s scientific sensibilities.
But there are lots of less extreme ways to cross the line that are still — by scientists’ own lights — harmful to science. Those “normal misbehaviors” emerge in a 2006 study by Raymond De Vries, Melissa S. Anderson, and Brian C. Martinson [1]:

We found that while researchers were aware of the problems of FFP, in their eyes misconduct is generally associated with more mundane, everyday problems in the work environment. These more common problems fall into four categories: the meaning of data, the rules of science, life with colleagues, and the pressures of production in science. (43)

These four categories encompass a lot of terrain on the scientific landscape, from the challenges of building new knowledge about a piece of the world, to the stresses of maintaining properly functioning cooperative relations in a context that rewards individual achievement. As such, I’m breaking up my discussion of this study into two posts. (This one will focus on the first two categories, he meaning of data and the rules of science. Part 2 will focus on life with colleagues and the pressures of production in science.)

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