Monthly Archives: November 2009

Deep Partisanship

By Peter Loewen. Cross-posted at A Shrewdness of Apes.

I spend a good bit of my academic life thinking about partisanship. What does it mean to be a partisan? How do partisans differ from other partisans and from non-partisans? What are the behavioural consequences of partisanship?

Our understanding of partisanship has changed over time. Beginning in the 1960s, academics understood partisanship to be a deep attachment to a party formed early in life which subsequently acted as a perceptual screen on the political world. Think of it as similar to religious affiliation. Individuals may stray from their familial religious affiliations, but for the most part these act as an anchor throughout the lifecycle and serve to influence how we experience and perceive the world.

This understanding of partisanship was later challenged by a ‘running tally’ perception in which partisanship was taken to be an active evaluation of the parties on offer, where an individual ‘updated’ their partisanship as new events unfolded and changed it as their affection for one party increased over another.

I think it’s fair to say that the first view has better stood the test of time, both inside American and outside. Principal in the defense of this view is a great book by Green, Schickler, and Palmquist called Partisan Hearts and Minds.

My own work has examined the behavioural and material foundations of partisanship in Canada. For example, I’ve shown that revealed material concern for the well-being of other partisans explains much of the decision to vote in Canada. I’ve also shown that material concern for others varies with our own and others partisanship. Finally, I am working on a larger (though still very preliminary project) on whether behavioural differences characterize different partisans. My own contribution is very small.

The most important contribution in recent years, and this is the point of this post, has just been made by Alan Gerber and Gregory Huber in this paper. Here’s the story: for a long time, we’ve had survey evidence that partisans have more positive economic expectations when their preferred party is in power in Washington. In other words, Republican partisans say they expect the economy to perform better when there is a Republican president than when there is a Democratic president. The same applies (in reverse) for Democrats. However, this could merely be an artefact of surveys. If partisanship really matters in a deep way, then what is needed is evidence that partisans behave differently when their preferred party is in office. Gerber and Huber provide evidence of this. They demonstrate that changes in the rate of expenditures at the county level following an election correlate with the partisanship of the county. So, more Democratic counties would increase their rate of spending more than Republican counties (or more accurately, decrease it less quickly, as spending is generally lower in the winter than in the fall) following the election of a Democratic President. The same applies for Republicans.

This is an extremely important finding as it shows that partisanship has deep behavioural consequences. It is not simply a tally of one’s preferences, but instead an affiliation which influences how one approaches not only the political but also the commercial world.


Minimal wiring in insect nest networks

By Yunkyu Sohn

Vavlerde et al. (2009) shows that ant nest networks exhibit near optimal wiring, the presence of efficient shortcuts generated by minimal physical efforts, which may be a consequence of natural selection.

Percolation in insect nest networks: Evidence for optimal wiring

Political Networks Paper Archive

By Chris Fariss

Many of the papers presented at The Harvard Political Networks Conference (June 11-13, 2009) are available at the Political Networks Paper Archive.

While you’re there make sure to check out these awesome papers (shameless plug for work by HNG members):

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2010 Complex Systems Summer School

By Chris Fariss

The 2010 Complex Systems Summer School at the Santa Fe Institute in Santa Fe, New Mexico is now accepting applications.

The Complex Systems Summer School offers an intensive three-week introduction to complex behavior in mathematical, physical, living, and social systems for graduate students and postdoctoral fellows in the sciences and social sciences. The school is for participants who want background and hands-on experience to help prepare them to do interdisciplinary research in areas related to complex systems.

All our work will benefit if a few of us attend.  We can blog from Santa Fe!

Hey Good Lookin: Does facial competence actually matter for election outcomes?

By Peter Loewen (crossposted at Ashrewdness of Apes)

Are politicians successful when they are better looking? Todorov and colleagues (here and here) created a stir by demonstrating that election outcomes can be predicted based on very quick evaluations of the “competency” of candidates’ faces. Could it be that voters are so superficial that a great share of them are merely persuaded by the attractiveness of candidates?

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Interactions between technology and social behavior

By Angela Nelson

I recently came across this article in Science by Alessandro Vespignani from Indiana University: Predicting the Behavior of Techno-Social Systems. Vespignani provides an interesting discussion of the multi-scale nature of networks, and how the types of behavior that occur at varying scales can differ widely in a given condition yet the system in its entirety is dependent on the interaction of behavior at all levels.  He also talks about what this means in terms of using computational modeling to predict network behavior, both in a steady state, and in times of social disruptions (such as pandemics or major natural disasters).

The figure below shows a simulated pandemic originating in Hanoi, Vietnam.

Fig. 2 Epidemic invasion tree obtained from the simulations of a pandemic originating in Hanoi, Vietnam. The nodes identify 3200 populations worldwide, and the directed links indicate the path along which the epidemic has moved from one population to the other. The color map from dark red to dark blue is according to the time ordering of the epidemic invasion. Simulations obtained with the worldwide epidemic and mobility model from (38).

Missing Data

By Michael Rivera

A project I am currently working on has a bit of missing data.  I found this useful and think it’s a good place to start if you find yourself in a similar situation.

“Much Ado About Nothing: A Comparison of Missing Data Methods and Software to Fit Incomplete Data Regression Models”

Horton and Kleinman (2007)