Wednesday, November 16, 2005

"Career-Killing Blogs" for Academics

An interesting article in Slate on what blogging means for academics, especially when tenure time comes around. The gist of it is that the academy doesn't know how to assess blogs when reviewing one's academic record (heck, they don't even know how to give marks for teaching online or using technology well in the classroom). However, the article suggests that blogs could perhaps become truly peer-reviewed publications, just as rigorous but more accessible than articles published in scholarly journals. The most intriguing idea is how to set up a peer-review system like that of slashdot or ebay. It might take time (think about how little some academics use technology in professional life as it is), but it could work! Seems like the Public Library of Science that the article mentions is a step in the right direction.

Wednesday, November 02, 2005

Freakonomics

Just finished reading Freakonomics; it's a really fast read, plus I've read so many excerpts from it in various sources that it felt more like re-reading! In its eminent readableness it reminded me of Blink, and whaddaya know, the author of Blink, Malcolm Gladwell, has a little blurb on Freakonomics' cover, "Prepare to be dazzled".

Anyway, well worth a read, shows how analyzing data can lead to some very surprising conclusions. The authors talk about how their results can overturn conventional wisdom (a phrase coined by John Kenneth Galbraith), which is "simple, convenient, comfortable, and comforting - though not necessarily true". Me, I find it more comforting to see the conclusions reached by data analysis, but I'm a geek.

However, I wonder about the use of regression analysis. I understand the basic concept, but it terms of how it really works, it might as well be magic to me. I remember reading Stephen Jay Gould's The Mismeasure of Man (what an exciting book, his humanist passion shone brightly through), in which, if I remember correctly, he talks about how measures of intelligence use flawed analyses (regression analysis? factor analysis? must reread!). Well, I followed along but ultimately I didn't have enough expertise to judge whether there were flaws in his argument. I had the same feeling of slight discomfort here - it sounded good, and made sense, but ultimately I took the authors'word for it.