Hirschman on Rational Choice Theory

January 26, 2010

Dan Hirschman, grad student at the University of Michigan, has a great post on rational choice theory.  It is framed as a critique, but I consider it wholly compatible with my defense of RCT. Human behavior is complex and different aspects of it will be best understood with different theories/models/levels of analysis.  See some of my previous posts on modeling here.


Graduate Student Fellowships at Facebook

January 25, 2010

Graduate students who are interested in large-scale networks should read this post by Tom Lento, who is a data scientist at Facebook (and a Cornell sociology grad), about Facebook’s new graduate fellowship program.

It’s pretty frustrating that, given the quasi-social science Facebook is doing, the listing does not explicitly mention social science disciplines, but I have gotten word that social scientists with appropriately strong computational skills (i.e. candidate should be a reasonably competent programmer) can be considered.

That said, it’s great that Facebook is willing to work with academics, especially graduate students, to do interesting things that might have some general scientific benefit (in addition to direct product benefit).  This puts them in the category of Microsoft, IBM, HP, Google, Yahoo, and other such tech companies, who also fund sizable graduate student internship programs.

Facebook has a treasure trove of micro-level interaction data.  If you want to work with that data, this might be the best way to do it.

Under-Appreciated Research, Inside and Outside Views

January 20, 2010

What are the currently under-appreciated research areas in sociology? I have my opinions, but I’d actually prefer to focus your attention on the meta-question: how might decide which research areas are under-appreciated?

There are two basic approaches, inside views and outside views. Inside views require understanding a phenomenon in terms of its component parts. In contrast, outside views require the often easier task of appropriately categorizing the phenomenon, a.k.a. choosing a reference class.

For examples, let’s return to the original question, where the phenomenon under investigation is “the appreciation/under-appreciation of research areas in sociology.” An inside view might look like the following chain of (questionable) reasoning: 1. the highest goal of sociology is to discover the knowledge which results in the greatest good for the greatest number. 2. Insects are numerous. 3. Little sociological research is done on insects. 4. Therefore, Insect sociology is under-appreciated.

An outside view might look like this:
1. It has been proven that, in the past, research areas more popular with women have been the most under-appreciated. 2. Therefore, its a good bet that research areas more popular with women are currently the most under-appreciated, even if I have no idea what those research areas are or why they are valuable.

My inside view and outside view arguments are pretty weak, they are just there to illustrate the concept of inside and outside views.  Can you improve on them or make a case for inside/outside approaches more generally?

teaching philosophy

January 19, 2010

So, i’ve seen the following proverb used a number of times for explaining how people teach:

Give a person a fish and you feed them for a day. Teach a person to fish and you feed them for a lifetime.

For me, i see that as a good start. i think the first is a partial aim of most classes (show them what’s out there – summarize findings, explain terminology, etc.), and the second is a highly valuable aim as well (getting the students to figure out how to answer questions for themselves).

But i think it’s still missing something with respect to my aim(s) for most classes. i also want to try to get students to a place where they can formulate some new questions on their own. In case you can’t make out the picture at right, it’s two people standing in the middle of a grassy field with fishing rods.* At the risk of mixing metaphors – even with the most powerful hammer, not everything is a nail. So in addition to the thoughts from the proverb above, i like to think of my approach to teaching as often also engaging the aim of teaching students why we fish in the first place, and hopefully enabling them to consider when a rake/rifle/bow&arrow might be a more useful approach than fishing. Does that work (on the metaphorical level) for the aim of getting them to formulate new questions of their own?

In related news, today marked the start of the second time through my undergrad networks class. Last semester went ok (though i am glad it was small), and that experience (along with a number of comments i got on- and offline in response to my post here about it) will hopefully make this time around (with enrollment ~4x last semester’s!) go a bit more smoothly.
* i am aware that they may be practicing casting, but it’s much funnier and more appropriate to my point to think that they are waiting for something to bite.

Influential Statisticians

January 17, 2010

Most quantitative social scientists, myself included, master particular statistical techniques, but have limited understanding of the breadth or history of statistical practice.  Academic specialization is necessary, but sometimes we could learn a lot by taking a broader view.  I found it interesting to learn a little more about some of the most influential statisticians and their contributions in this article by Daniel Wright: “Ten Statisticians and their Impacts for Psychologists.”

Though I enjoyed Wright’s piece, one thing I felt was missing was a connection to philosophy and sociology of science.  What are the goals of empirical research in the social sciences?  How have the methods these statisticians invented changed social science, and science more generally?

I recommend Seth Roberts’ comments here and Andrew Gelman’s comments here.

Wright, D. (2009). Ten Statisticians and Their Impacts for Psychologists Perspectives on Psychological Science, 4 (6), 587-597 DOI: 10.1111/j.1745-6924.2009.01167.x


January 15, 2010

My engagement with the blogging world (probably like most folks’) goes in cycles. Ironically i think that most often, the times i am absent from online discussions actually coincide with my least productive times in my research/writing, and vice-versa.* Similarly, my excitement about any particular blog (reading or writing) waxes and wanes as well. For a while now, the blog i have been most interested by, most likely to flip to when i get notification of a new post, and simply find to be my current favorite read is Gabriel Rossman‘s Code and Culture. i know that we have it linked over there in the blogroll, but i think that it is often something anyone reading this one would also be interested in. The main reason for this post was thus simply – just in case you aren’t already reading it – i wanted to take a moment to send you in that direction.

*Accordingly, yes, you would be correct to assume that i have knocked a few things out in the past week or so, coinciding my recent flurry of posts. Wohoo!

what’s in a tie?

January 12, 2010

i recognize that my last few posts really haven’t done much for hitting the target of the theme of this blog. So, with that i give you Stephen Colbert. No seriously, it’s relevant i promise. James Fowler’s on pitching his book with Nicholas Christakis: Connected.* In the interview he makes the shocking revelation that social networks aren’t new to social network sites like Facebook.** Gasp! He then starts to get into a little bit of the “what can we learn about real world social connections from Facebook?” question in the interview.
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January 11, 2010

Yeah so, publishing in Nature is something i’d like to knock off the list at some point (i thought we had it nabbed a while back, but that particular paper now seems stuck in permanent limbo, but i digress); unfortunately it hasn’t happened thus far. If i could accomplish that goal with a piece like this one, i think i would be doubly excited. The title for the letter is “Fetal load and the evolution of lumbar lordosis in bipedal hominins,” which is roughly translated by the Ig Nobel Prize* announcement it won (see here, scroll to Physics Prize) as “analytically determining why pregnant women don’t tip over.”

* described as being “For achievements that first make people LAUGH then make them THINK.”

In hindsight, how would you have prevented the financial crisis?

January 7, 2010

Arnold Kling was asked:

With regard to the recent financial crisis and current economic recession – if you were given the power to go back in time and change only one thing in an effort to prevent the crisis and recession, what year would you choose, and what one thing would you change?

He answers here. You also might want to check out his new book with Nick Schulz called Poverty to Prosperity: intanigible Assets, Hidden Liabilities and The Lasting Triumph over Scarcity.  Much of it consists of interviews with highly noted economists.  I’ve only had the chance to read a few chapters so far but I’ll definitely look at it again when I have a little more time.

Magic and Mathematics

January 6, 2010

This past weekend I found myself listening to This American Life, a quirky show that tells a variety of stories about the American experience. The most recent show included a discussion of the potential and pitfalls in economic forecasting. And, as it turns out, predictive models of the national economy aren’t very good- with margins of error wide enough to straddle the range from “sluggish with rising unemployment” to “robust with decreasing unemployment.” That’s a little bit like going to your doctor and being told that, given your test results, you’re either going to life for another thirty years or be dead in six months. Most of us would probably not find such a prognosis terribly useful. Yet, what emerged on the show was not only an acknowledgement that economic forecasting is chancy at best- there was some discussion actually that predictions should be made along the lines of “growth will be two-ish percent”- but a wry commentary on the degree of precision in those estimates. Indeed, while the margin of error is so wide as to encompass both boom and bust, the predictions themselves regularly include two or more decimal points. It is as though the doctor has said that you will live for either thirty years and one hundred days, or six months and eight hours. By the time the range is that large, including the extra bits seems a tad silly. Yet, pointless or no, the precision is in the estimates and, more to the point, is actually demanded by the consumers. Even though the people who use these forecasts are aware of how inaccurate they can be they nevertheless seem to want all those extraneous decimal points.
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