Lynne Kiesling
While noodling about this morning over my cup of tea, I wandered into some places that I should mention. Some are new to me, some are places I go and just don’t mention.
1. Grant McCracken’s This Blog Sits At the Intersection of Anthropology & Economics. One of those funny things, really; I read it regularly, but somehow it hasn’t gotten on to the links list.
The one that I got linked to from elsewhere today was “Blogging: what’s it for, how it pays”. Nice quote:
Blogs are experiments. Each of them says, in effect, what happens to this way of thinking if we apply it to a variety of topics for an extended period? Do the ideas flourish or wither? Do they evolve or merely repeat? Do they scale up in their complexity, or, forgive me, bog down.
If things go well, I guess, blogs go off like an alpine ecosystem: tiny flora make a platform for minor flora which make a platform for major flora. Pretty soon, there?s a forest on a slope. Actually, in the best case, blogs terra form. By steadily converting ambient resources, own and others, they create a sustainable intellectual space where none before was possible. They make their own worlds, and so prove the possibility of these worlds. They ?discover? worlds by creating them. …
One of the key questions here (?loose concept/sliding metaphor? alert) is whether the blog is actually ventilating. Anyone can build a little world sui generis. Just bang away at our favorite topics often and at length, and Bob?s your uncle. But good blogs inhale data before they exhale comment. And we expect them to address the big issues in a timely fashion (the presidential elections, say) even as they show a certain imagination and versatility in finding issues not now on readers? radar.
2. The Long Tail by Chris Anderson, Wired Magazine’s editor-in-chief. I’ve heard this long tail idea swirling around over the past couple of months, read the article from Wired, discussed the ideas over dinner wtih the KP Spouse a few times. So this journal-to-a-book is a good find.
3. Signal + noise from Christopher Genovese, a statistics professor at Carnegie-Mellon University. Of particular interest to me is his most recent post, which is basically a statistical analysis of how well you know what you don’t know.