A recurrent feature of game-theoretical economics, political science and sociology is the principal-agent problem. Many phenomena in the social world can be described in terms of the (various) theories of principals and agents. Want to understand how Southwest Airlines broke into the industry? Why presidents do not exit losing wars? Why it was an advantage for Kennedy in his standoff with Khrushchev to have a “rogue” general who favored nuclear war? Why corruption is not only a collective action problem? Principal-agent theory is here to help! A principal sends an agent to do a task, under some kind of contract or agreement, establishing a relationship subject to certain constraints, and open to certain possibilities. If we can describe these constraints and possibilities, we can explain a lot. Does agent know more than principal? Does principal have the capacity to punish agent, reward agent, or both? And so on.
I wrote a letter to the NY Times in response to Richard Arum and Mitchell Stevens’ “What is a College Education in the Time of Coronavirus?“. Unsurprisingly, the letter was not published, so I offer it here as a conversation-starter on lessons we should and shouldn’t learn from higher education’s current situation.
It looks like we’re in another “economic downturn,” and many PhDs are understandably worried about what it means for the future of the sociology job market. I haven’t been to Delphi or stayed at a Holiday Inn Express, but I am knee-deep in historical ASA reports. Here’s what the data look like for how the 2008 recession affected the sociology job market in the US. Spoiler: I don’t think the market ever recovered, and more hopeful estimates say it took 4 years to recover.
It’s hard to even begin blogging about something so vast and ever-shifting. This post is just going to be a short pointer to a couple of the best pieces I’ve seen covering the social and economic angles of the pandemic.
The following is a guest post by Juan Pablo Pardo-Guerra.
Topic models are fast emerging as a workhorse of computational social science. Since their introduction in the late 1990s as part of a larger family of classification and indexing algorithms, they have grown into one of the most common and convenient means for automated text analysis. Not too long ago, using topic methods confronted scholars unfamiliar with programming with steep learning curves: even the simplest implementations required some familiarity with coding in addition to a good deal of patience. Today, by contrast, topic modeling is available as part of point-and-click desktop applications (e.g. Context) and can be installed in widely used statistical analysis packages (e.g. Stata). The relative ease, scalability, and intelligibility of topic models explains, perhaps, their quick adoption across sociology, political science, and the digital humanities. Indeed, to say that topic models are the OLS of text analysis wouldn’t be too much of an exaggeration.
From 2016-2019 I had two positions that have taught me a lot about academic leadership and organizations. I led the process of redeveloping UNC’s General Education curriculum, “IDEAs in Action,” which was approved in April 2019; and I sat on the American Sociological Association’s (ASA) elected Council. These two blog posts are intended to explain some of the things I’ve learned from both of these experiences.
This post will deal with what I’ve learned from three years serving on the ASA council. The previous post dealt with my role leading UNC’s general education curriculum redesign.