The Quantitative Peace

While the IR people are away, the Americanists will play.

Editor's note: This is a guest post by Joshua N. Zingher, a doctoral candidate in the Department of Political Science at Binghamton University. The content of this post is based on Josh's paper, ‘An Analysis of the Changing Social Bases of America's Political Parties: 1952-2008’, appearing in Electoral Studies. This piece is cross-posted at the London School of Economics' USAPP Blog, which can be found here. 

 

Demographic changes mean that traditional Republican constituencies are shrinking as the Democrats’ grow.

It is difficult to discuss electoral politics in the United States without talking in terms of social groups.  Journalistic accounts of party competition often stress the important role that specific constituencies play (such as the “evangelical” or “Latino” vote) in determining the outcome of presidential elections.  A great deal of political science research has shown that these social cleavages structure party competition.  However, the political importance of these social cleavages can change, which can lead to a reshuffling of the social bases of the party coalitions.  In addition, demographic changes also have the potential to dramatically reshape the political landscape, as new groups enter the electorate and the ratio of existing groups’ changes.  I am interested in how changes in the cleavage structure and changes in the ratio of groups work in conjunction to transform electoral coalitions.  In new research, I investigated two related questions: what group memberships influence individual level voting behavior and how has the number of votes each political relevant group contributes to the party coalitions changed over time?

 

Identifying the Group Bases of Party Support 

So what groups are politically relevant?  To answer this question, I conduct a multivariate statistical analysis utilizing nearly 60 years of American National Election Survey (ANES) spanning 1952 to 2008.  I utilized group memberships as independent variables and vote choice as the dependent variable.  The battery of group memberships included variables for class, race, ethnicity, region, education, birth cohort and age. I define politically relevant group memberships as those that exert a statistically significant influence on individual level vote choice.  I ran a separate regression for each decade, which allowed me to assess whether the effect of specific group memberships have changed over time.  The substantive results of these models are displayed in Figure 1 below.

 

Figure 1 – Predicted effect of group membership on vote choice in presidential elections

 

 

The results of the analysis displayed in Figure 1 demonstrate that the following group memberships lead individuals to be consistently and statistically significantly more likely to support one party over the other: 

 

Table 1: The Core Democratic and Republican Social Groups 

Democratic Groups	Republican Groups
African Americans	Whites
Latinos	Protestants
Catholics	Weekly Church Attendees
Union Members	Southern Whites
Non-Religious	Men
College Graduates
Women Jews

 

This analysis highlights the continuity and change that characterizes the parties’ social bases.  Some groups have been stable members of a party coalition for the last 60 years.  African Americans, Catholics, union members and Jews have all been consistent members of the Democratic coalition while whites and Protestants have reliably favored the Republicans. 

Yet, other groups’ political leanings have changed considerably.  Whites in the Southern United States were once reliably Democratic voters; today they are one of the most solidly Republican constituencies.  The divide between the religiously devout and the secular has also become more politically important in recent elections.  Non-religious voters have become increasingly likely to vote for Democratic candidates while weekly church attendees have become more likely to support Republicans.  Similarly, a partisan “gender gap” emerged in the 1980s.  Men have become significantly more likely to vote for Republican candidates while women have become more likely to support Democrats.  In sum, many traditionally politically important social cleavages have endured (e.g. black/white) while other cleavages have become politically important only in recent decades (secular/religious or female/male).

           

Group Contributions and the Importance of Demographic Changes

The preceding analysis established what group memberships significantly influence vote choice, however, simply understanding what group memberships shape individual level voting behavior paints an incomplete picture of electoral change.  Winning an election is not about having core groups of loyal supporters.  Rather, parties must be able to obtain a majority of votes in order to win elections.  Thus, any process that leads to a party gaining more or less from a specific social group is potentially politically consequential.  Figures 2 and 3 show my calculations for each group’s contribution to the Democrats’ and Republicans’ party coalitions, as measured as a proportion of the party’s total votes. There have been considerable changes in the size of group contributions to the party coalitions—many of which highlight the important role that demographic shifts play in reshaping the party coalitions. 

 

Figure 2 - Group contribution as a proportion of Democrats’ total votes: 1952-2008

 

 

Figure 3 - Group contribution as a Proportion of Republicans’ total votes: 1952-2008

 

The Democratic Party has been obtaining an increasing proportion of its support from groups that are growing as proportion of the electorate, such as Latinos, college graduates and the non-religious. In addition, increasing turnout among Latinos and African Americans has also led to the size of these groups’ contributions to the Democratic coalition.  The Republican Party is being forced to confront the opposite scenario—many Republican groups, whites, Protestants and weekly church attendees, are making up a continuously shrinking proportion of the electorate.  Thus far, the Republican Party has been able to offset demographic changes via high turnout among their core groups as well as through winning an increasingly large majority of the Southern white vote.

So what are the conclusions can be drawn from this analysis? Firstly, the group sources of party support are dynamic, the political relevance of certain social cleavages ebb and flow across decades, which is evidenced by the changing relationship between group membership and vote choice.  Secondly, demographic changes can be politically consequential.  The Republican Party is currently in the undesirable position of having to find new sources of electoral support in order to remain viable in future elections.  The Republican Party’s need to find new sources of electoral support has come about not as a result of the loss of electoral support among loyal groups—rather, the Republican Party must find new sources of electoral support simply because traditionally Republican constituencies are making up a shrinking proportion of the electorate.     

 

 

 

Historical Cartography

Uri Friedman at the Atlantic has a nice piece entitled "12 Maps that Changed the World." It's based on a book by Jerry Brotton, professor of Renaissance Studies at Queen Mary University. It's worth checking out if you haven't seen it already. This article is interesting for a few reasons. First, it gives you some sense as to how views of the earth have changed over time. Second, Friedman's snippets for each map help to show how politics, culture, and religion all influenced the evolution of these views. And related to that previous idea, it points to that ever-present issue of measurement. Social scientists aren't the only ones who confront these kinds of issues, and information we now tend to assume away as being relatively objective and simple to define/convey (e.g. geography) can actually be more complicated that we might first think:

"All cultures have always believed that the map they valorize is real and true and objective and transparent," Brotton, a professor of Renaissance studies at Queen Mary University of London, told me. "All maps are always subjective.... Even today’s online geospatial applications on all your mobile devices and tablets, be they produced by Google or Apple or whoever, are still to some extent subjective maps."

There are, in other words, no perfect maps—just maps that (more-or-less) perfectly capture our understanding of the world at discrete moments in time. 

At this point in time I suspect the subjectivity associated with cartography is probably less a matter of relative size and space, and more a matter of content (i.e. borders, landmarks, etc.). Friedman addresses this a bit when he talks about Google's map-making efforts in #12.

Map #4 also stood out to me:

What's most striking about this Korean map, designed by a team of royal astronomers led by Kwon Kun, is that north is at top. "It's strange because the first map that looks recognizable to us as a Western map is a map from Korea in 1402," Brotton notes. He chalks this up to power politics in the region at the time. "In South Asian and Chinese imperial ideology, you look up northwards in respect to the emperor, and the emperor looks south to his subjects," Brotton explains.

There's also a clip from the West Wing attached to Map #11, the Peter's Projection. Something for everyone.

Educational Attainment and Race in Alabama

A part of my responsibilities as a post-doc here at Alabama entails helping faculty with seeking out external funding for projects. One of these projects has involved developing a program to promote educational outreach throughout the state. In the course of this work I've been digging through some data on educational attainment rates in Alabama. In terms of learning about the political and economic characteristics of my new state, this has been an informative exercise. I also think it's helpful in illustrating the benefits of digging through your data, and helps to shed some light on the benefits of considering the distribution of your data more carefully, and so I thought I'd write a quick post on the subject. For the purposes of this post I'll be drawing on data collected from the American Community Survey's 2006–2010 five year population estimates. 

The mean percentage of Alabama's population holding a bachelor's degree or higher for this time period is 21.7%.  Compare this figure with that of my home state—New York's overall rate is 32.1%. This is a fairly large disparity, but further disparities emerge when we begin to disaggregate the data by race. The graph below shows the mean value of this same variable across the black and white populations of both states. 

From this we can see that the total values mask some important differences between groups within each state. In both cases the college attainment rate of the white population is slightly higher than the overall mean value. Alternatively, the attainment for the black population is significantly lower than the overall mean value in each state. Even New York, which on its face appears to have a significantly higher overall college attainment rate, is not much different from Alabama when we compare black college attainment rates with Alabama's values. 

Even when disaggregating the data in this way, we often still lean on the mean value pretty heavily. The distribution of the data around the mean can be incredibly informative as well, but we don't often pay as much attention to this as we should. Below I present a quick illustrative example of why this can matter.

Looking at Alabama's data again, I have drawn on county-level college attainment data for both groups.

Looking back at the first graph we can see that the statewide mean white college attainment rate was about 24%, and the statewide black attainment rate is roughly 14%. Looking at the county-level distributions can help us to get a better grasp on educational attainment rates throughout the state. In the case of white attainment, we can see that the distribution is slightly skewed towards the low end, but the lowest value in the distribution is around 8–9%. Alternatively, the distribution of black college attainment rates at the county level is more heavily skewed, and the lowest value in the distribution is considerably lower than for the white attainment rates, as shown in the preceding graphs where the X-axes are held constant to help make the figures more comparable. In fact, .30% is the lowest black attainment rate recorded in the data. 

Looking at the distribution of the data in addition to the mean values for these different groups can provide some additional insights into the substantive issues we're interested in. In this case, it's already apparent from considering the mean values that there are disparities in the college attainment rates of the black and white segments of the state's population. However, these values may actually underestimate the magnitude of those disparities. Though the distribution for white attainment rates is still skewed, it's floor is considerably higher than that of black attainment rates. In fact, by my count there were 14 counties in which the recorded black attainment rate was lower than the lowest recorded white attainment rate. The maximum for each group is roughly the same, however. Areas around Tuscaloosa, Birmingham, and Huntsville have fairly high college attainment rates. But these areas are highly unrepresentative when considering the state more broadly. In fact, although the mean statewide black attainment rate is 14%, the majority of counties fall well below this figure. And while most counties also fall below the mean on white attainment rates, there are, comparatively, more counties falling above the mean. All of this suggests that the mean statewide black college attainment figures are more heavily influenced by outliers in the data than are white attainment rates.  

Lastly, looking at these plots reveals another important feature of the distributions—the variance. The variance in white college attainment rates is 66.2. The variance in black college attainment rates is nearly half that, at only 37.5. This tells us that not only are black college attainment rates lower than white attainment rates, but they are more uniformly so. To put it differently, there is greater dispersion in white college attainment rates, while black college attainment rates are more tightly clustered around lower values. This is made apparent by looking at the two preceding graphs. Though both are skewed towards the lower end of the X-axis, white college attainment figures are less tightly clustered here, as I mentioned above.

This is an issue that I'll come back to in the future, but for now it seemed like this was a useful example for illustrating the importance of familiarizing yourself with the data that you're working with, and how relying less on simple mean values can reveal interesting features of the data you're working with. Bear Braumoeller has an interesting Political Analysis piece about examining the variance, which is worth checking out. More substantively, I also think that this exercise helps to more fully draw out the disparities that may exist between social groups. Relying on simple indicators of central tendency can be useful in some contexts when we want to quickly convey bits of information, but these figures can also be misleading. At the very least, they don't always tell us the full story.

 

Teaching Introductory Graduate Methods: Some Ideas About Understanding Sampling Distributions

Everyone has their own way of teaching methods, but in this entry I thought I’d share a brief exercise that I thought worked well. This code was developed when I was the teaching assistant for a second-semester methods class focusing on regression. Specifically, this was a section of the class from the first few weeks that dealt with two things: first, showing/repeating the idea of a sampling distribution, and second, showing some introductory code on loops and graphics.

The code uses the ggplot2 package for R. This software, and this package, have (in my experience) a somewhat steep learning curve so starting slow is important, even in the second semester. Equally, the concept of a sampling distribution is something that takes a while to click with most people who don’t have a statistical background. So what I’m trying to do with this code is show some basic graphics, and also introduce sampling distributions by ‘bringing one to you on a plate’.

            The first part of the code simulates ten rolls of a (pseudo) six-sided die:

cenlt<-vector(length=10)

for (i in 1:10)
{

            x<-runif(10,1,6)

            cenlt[i]<-mean(x)

}

cenlt

Here we create a vector, called cenlt (named for the central limit theorem), of length ten. We don’t give R any instructions about what to put in this vector, so if we inspect it (typing “cenlt”) it will display ‘FALSE’ ten times. We leave this empty vector to one side. Then we create a new imaginary conveyor belt, telling R to sit beside the conveyor belt and perform the same operation every time the belt rolls past, which it will do ten individual times. 

            The operation R will perform is to create ‘x’, which is a set of ten numbers, each randomly sampled from a uniform distribution between 1 and 6. We then take the mean of this set, and store it as a new element of cenlt. When we’ve done this ten times, then, cenlt will be full. We then display cenlt. We can actually display it a little bit more attractively if we graph it: 

library(ggplot2)

p1<-ggplot()

p1<-p1+geom_histogram(aes(x=cenlt),binwidth=0.2,
linetype=1, alpha=.3, color="black", fill="red")

p1<-p1+ ylab("Count") +
xlab("Sample Mean") + xlim(c(0,6)) + ylim(c(0,6))

p1<-p1+opts(title="Distribution of Sample
Means")

p1<-p1+geom_segment(aes(x = 3.5, y =0, xend =
3.5, yend =6))

p1

            The first line creates a new object called p1, which we set to be a graph object. Then we take it, and add another layer. The second line tells it to fill the graph with the shapes necessary to make a histogram: aesthetically, this means an x-axis defined by the values of cenlt. We ask for the shapes to have a solid black outline (linetype = 1, color = “black”) and to be semi-transparent and red (alpha = 0.3, fill = “red”). We then add a line showing the expected mean (geom_segment) as well as other details. 

            This code was then followed by a discussion of what each element of ‘cenlt’ represented. Each was a mean. So the mean of cenlt was a ‘mean of means’, and so cenlt has its own distribution: the distribution of means of ‘x’, and if we consider each x to be a sample, then seeing cenlt as the sampling distribution is relatively straightforward. The code can then be tweaked to make ‘x’ bigger, or to run ‘x’ more times, and discussing each of these options helps elucidate the idea of a sampling distribution. Changing the distribution away from uniform can also be useful. We also got some good discussions out of manipulating the basic parameters of the graph (the axis labels, the colors and binwidth of the histogram), and then later by switching the geoms to different options. All in all, this was a useful exercise that led to some good discussions, and helped introduce the ideas of sampling distributions, loops, and statistical graphics.

 

How Do You Review?

I’ve been sending articles out for review for a few years now, and I’ve also had the opportunity to review several papers for journals. Having been through each side of the ordeal, I’ve begun to form some opinions on the peer review process as a whole. This is something other political scientists have written extensively about. For example, Michael Allen recently addressed the issue on this blog, and Nathan Jensen recently wrote an interesting piece about one of his paper’s journeys through the political science peer review process.  However, some of my recent experiences have prompted me to think about the process from the vantage point of the reviewer. Most of what I can recall reading on the subject tends to focus on the process as a whole, or discusses the process from the point of view of the submitter, rather than the reviewer. So I thought I’d reflect on my experiences and what practices I’ve tried to incorporate into my reviews.

1. Take reviews seriously: This might seem like an obvious point, and it's one Jensen makes in his post, but for anyone who has been through the process you know you can’t always take this for granted. We’ve all gotten terrible reviews in some way shape or form—some of them are condescending in their tone, some of them seem to address topics or ideas that are completely irrelevant to the paper in question (even after much reflection), some of them are incredibly short, and some of them are just wrong. And these points just concern content. Some reviewers just don’t respond to review requests from journals, and others don’t seem to get around to the review until several months after the paper was submitted.

For the most part, all of these things are well within the power of the reviewer to control. I say “for the most part” because sometimes comments or suggestions made in a review may be wrong, but I’d like to believe reviewers are not dishing out incorrect information on purpose. And maybe sometimes people just aren’t communicating their thoughts well, thereby leaving the reader with no idea as to how those thoughts apply to their paper. Also, sometimes life does get in the way, causing unexpected delays. But, quite often, you as a reviewer can control these sorts of factors.

The review process can and does put a burden on journal editors and reviewers—there’s no question about that. As Jensen notes in his post, senior scholars in particular can be swamped with review requests. But reviewing is probably one area in which scholars can have the greatest impact on the professional fortunes of other scholars. And I don’t mean to imply that reviewers should fail to reject a paper just to provide a boost to someone else’s career. Not every paper deserves to be accepted or given a revise and resubmit, but editors rely to varying degrees on the advice given to them by reviewers. We also know that there are plenty of hard working people out there who face rejection after rejection, many of which are for really silly reasons. If you’re going to reject a paper, the author deserves to know why. A flippant one-line response is not helpful to anyone.

I typically try to get my reviews back within a month or two, if possible. I'm still pretty early on in my career, at a point where not many people know much of my work, so it's probably pretty easy for me to meet this goal as compared to more senior scholars. On the one occasion that I've known in advance that I wasn't able to get reviews back in a timely manner, I’ve communicated this to the editor. It’s easy to blow this responsibility off—I mean, this isn’t your work, right? You are taking time away from your own busy schedule to review someone else’s work. Still, more likely than not you are asking others to do the same for you. 

2. Be clear and detailed: Along the lines of the previous point, a lack of detail in a review doesn’t help anyone. I once received reviews on a paper that ran the gamut from a single sentence saying to publish the article as is, to a rather lengthy, and in no uncertain terms, reject. As nice as it was to see that someone enjoyed your paper so much that they suggested accepting it, I’m not sure that such a brief reply helps. Truthfully, some of the more lengthy and critical reviews provided me with ideas for changes that I really do believe made the paper a better one.  

More often than not, papers are going to be rejected, and reviewers should know this. Even if you like a paper so much that you want to see it accepted as is, or with minor revisions, there will usually be at least one other reviewer on a given paper, and it is quite possible that this other reviewer will have a very different take. No paper is perfect, so it can be helpful to know why a reviewer believes that the strengths of a paper outweigh any weaknesses. Especially when other reviewers are less supportive. It’s also helpful to be able to compare reviews to see if there are any common themes/complaints that are popping up across readers. Given the high rate of rejection, I think it’s important to remember that it’s not really just about the one or two reviews that the author receives on a given round of submission. Setting aside for a moment the fact that one person can get the same paper to review over the course of that paper’s journey through the review process, if reviewers are clearly raising the same concerns through multiple rounds of reviews that might be a pretty good signal that something needs to be changed. Sometimes these sorts of things are easy to spot from one set of reviews, and at other times they’re not, but the authors can’t tell if the reviewer doesn’t provide the detail. Given the high probability of rejection, if you, as a reviewer, think that a paper's strengths outweigh its weaknesses, a failure to highlight those very features could result in them being erased in future rounds of reviews.

I’ve gotten to the point where I offer a brief statement at the beginning of the review in which I explicitly state whether or not I’m recommending acceptance, rejection, etc. I also try to offer a brief summation of what factors I’m considering in making this recommendation. I also try as hard as possible to not waver in my judgment—if you have “mixed feelings” or you “could be convinced” that a paper could be worthy of publication, don’t try to pass the buck to the editor and the other reviewers. Just recommend an R&R and move on. Nothing says you have to accept the second or third round of revisions, but given how competitive the review process is, this kind of waffling is effectively the same thing as rejecting the paper outright, and it's probably not all that helpful to the author.

Beyond the introduction, I also try to clearly identify each individual point that I want to address. And yes, this often involves an enumerated list and/or bullet points. To some extent I think this is just a matter of style. However, it can be difficult in a meandering review to discern the exact points that the reviewer wants you to address, and as much as it is the author’s responsibility to take their revisions seriously, it is also the reviewer’s responsibility to make clear those points that need addressing. Furthermore, we hold ourselves to a pretty high standard when it comes to organizing our thoughts and arguments in the context of an academic paper, so why shouldn’t it bethe same in reviews? It is, after all, all part of the same, broader, knowledge-generating process.

3. Offer constructive criticism: Again, this seems like an obvious one, but you can’t take it for granted. We spend an awful lot of time in college and graduate school learning/practicing how to pick apart other people’s arguments. So while pointing out the flaws in someone’s article is certainly an important part of the review process, I also think it’s equally important to be able to point out its strengths.

For the most part, my experience on this point leads me to believe that most reviewers are pretty good about this. However, I have received reviews that are highly critical, with little in the way of constructive commentary. "Complainy" might be the most appropriate made-up adjective to describe these reviews. If you as a reviewer think that there are some deficiencies with an argument or method, you need to spell that out for the author. If such deficiencies were clear to all, then they probably wouldn’t be in the paper to begin with. Further, I think the degree to which any flaw is damning to the overall article is contingent upon the availability of feasible alternatives. If you don’t like a measure that the author uses, don’t just complain and then move on. At the very least, ask the author to clarify whether or not superior measures are actually available. If you are aware of one that you believe is superior, then please share it and explain why you believe it to be better suited to the analysis at hand. Again, this is a collaborative venture, and part of the review process is being able to access the knowledge of other scholars.

I would also say that personally, as a junior scholar, I really do appreciate a good review when I get one. Some people have clearly taken the time to think about my work, and I appreciate it. As I said before, I’ve been fortunate enough to get some great feedback that I have subsequently incorporated into my work, and I do think the work is better for it. Criticism accompanied by constructive feedback and advice generally seems to be more helpful than merely pointing out the faults of a particular project.

4. Be transparent when it comes to your own limitations: As I stated above, sometimes reviewer comments are just wrong. Sometimes this is an honest mistake, and the reviewer is trying to offer sincere advice or criticism, but just gets it wrong. But, as an author this can be incredibly annoying—particularly if some factually incorrect statement could have been a major contributing factor to your paper’s rejection. If I’m reviewing a paper and I’m unclear about a measure, statistic, or method, I typically try to be entirely transparent when it comes to my own ignorance on the matter. Now I'm pretty confident in the substantive and methodological training that I received in graduate school, but this doesn’t mean I’ve mastered every analytical approach or estimation technique. Nor does it mean that I can’t learn even more about those topics and methods that I have been exposed to. Indeed, I’ve learned a lot over the past seven years, but as this SMBC comic so nicely conveys, sometimes expanding your knowledge base can raise new questions. So, when you think you don’t know, or you know you don’t know, just say, “I don’t know.” Feel free to even pose a question on the issue to the author in your review. After all, there is a certain irony in the idea that certain people, having devoted themselves to an industry that (ostensibly) is based on the discovery and accumulation of knowledge, would be so reluctant to utter those three words.

I'm sure senior scholars may have a different take on some of these issues. As I said, I'm still very early on in my career, so I'm not facing the same kinds of pressures from as many sources as they are. I don't have to deal with dissertation committees or a never ending stream of review requests. Still, I don't mind reviews all that much. They can provide me with some insights into what people in my general area of expertise are working on, and they often lead me to read works that I've not previously noticed or thought much about. But perhaps my views will change given time. 

 

 

 

 

 

Political Science and Scientists in the News

Just a quick link to this Atlantic article. It features several works by political scientists on why and when the public is likely to support military action. Complete with graphs and everything. 

 

*Picture taken from the aforementioned and linked Atlantic article. 

Follow-up

Just a quick follow-up to yesterday's post. Chad sent me a link to this paper that was recently posted on AJPS' early view. I've not read the entire article yet, but it seems apropos given the subject matter of yesterday's piece. 

Tom Coburn's Grudge, Part II

Via Jennifer Diascro's Twitter feed: The Economist has an article up addressing the specific targeting of Political Science Research by Senator Coburn. The article addresses a point that I've brought up a couple of times in the past (see here for example). Specifically, why only political science?

The Economist:

The real debate seems to be over what is of value. For many Republicans the answer is nothing having to do with political science. Yet it is hard to see how that discipline is any more frivolous than—or even all that different from—economics, sociology or anthropology.Mr Coburn's measure wouldn’t touch NSF funding for other social sciences. But this is the fourth time since 2006 a Republican has singled out political science for cuts.

If we look closer at those efforts, the picture becomes a bit clearer. Mr Coburn, for example, has particularly objected to studies on American attitudes to the filibuster, at a time when Republicans are using the filibuster routinely. Mr Flake had likewise complained about research on climate-change negotiations. When Mr Coburn first proposed cutting off funding in 2009, he complained that NSF money had gone to fund The Human Rights Data Project, which, he noted, had “concluded that the United States has been ‘increasingly willing to torture enemy combatants and imprison suspected terrorists,’ leading to a worldwide increase in ‘human rights violations’ as others followed-suit.” Mr Coburn even groused that Paul Krugman had received NSF grants more than 15 years earlier. Presumably that was because Mr Krugman went on to become a liberal columnist and not because the research won him a Nobel prize.

In all of these cases, the research risked calling into question the wisdom of policies supported by the Republican Party. In none of the cases did Republicans argue that the studies were flawed. They appeared to simply object to financing research that might contradict their point of view.

I would add that my impression is that political science research is probably the one field that is most likely to draw upon and combine insights from all of these other fields. Perhaps I'm mischaracterizing the work of scholars from these other disciplines, but if this view is accurate then it further hurts the credibility of Coburn's claims to be going after wasteful spending. If the idea is to get as much bang for our buck as taxpayers, political science seems like exactly the right field to invest in. But does this matter? Probably not. Most people just don't know or care enough about this to really see the problem, and for these people Coburn's credibility is really a non-issue, so he can still claim to be simply fighting the good fight against bloated government budgets. 

Finally, I'd urge all of my Americanist and comparativist colleagues to start building up the national security implications of their work. After all, we must remain ever vigilant to safeguard our democratic institutions from infiltration by the communist scourge. Maybe ANES can just add a question asking "Are you a communist spy?" or "Are you a terrorist?" and Coburn will be satisfied. 

Ice Breakers

I have posted a list of ice breaker questions below that can be fun to use during the first week of classes. Feel free to comment if you have any more suggestions!

1. If you could meet 3 people, real or fictional, who would they be?

2. Name a political event that has impacted your life. Explain how it has impacted your life.

3. What was your last Facebook status update?

4. Tell us something your parents do not know about you.

5. Write two truths about yourself and then a lie. (Then the class decides which facts are true and which one is a lie).

Observations from Jury Duty

I had the opportunity to serve as a juror this week for a case in Ontario County, NY. This was the first time I served on a jury. I thought it would be funny to do something like this to get out of it, but now I am really glad I served. It was a great experience. I made several observations about the process, and now that the trial is over, I can talk about it!

Jury Selection

Jury selection was a long and tedious process. I was actually quite surprised at how well the judge, prosecutor, and defense attorney handled it. They had to ask 42 potential jurors the same questions over and over, and this lasted about 5 hours. Despite the long and repetitive nature of this procedure, the judge, prosecutor, and defense attorney were polite, friendly, and energetic when they questioned each potential juror. I think this made it easier for everyone to relax and be patient through the entire process.

Next, before this whole process began, I was under the assumption that during jury selection, lawyers tried to choose jurors who were sympathetic to their side. This is probably because I am quite cynical- instead of following the letter of the law, I expected the lawyers to try to manipulate the verdict by stacking the jury with people they could easily manipulate. In this particular case, it does not appear that lawyers did this at all. Instead, the lawyers simply tried to look for jurors who were, in the very least, not biased against their side. For example, the prosecutor had one witness who was disabled and needed assistance testifying. He asked several questions to determine if potential jurors were biased against testimony from witnesses who were disabled, something he clearly wanted to avoid. In addition, the defense attorney knew that the prosecutor would call several law enforcement officials to testify. She asked several questions to determine if potential jurors were biased in favor of witnesses who worked in law enforcement, something she clearly wanted to avoid.

Next, several of the potential jurors were surprised to learn that it is up to the prosecution to prove beyond a reasonable doubt that the defendant is guilty, and that the defense does not have to present any evidence at all. Several of the potential jurors were confused why a defendant would not have to provide evidence. They assumed that if a defendant did not testify, this meant the defendant was guilty. Clearly those jurors were not selected, since they had a clear bias against the process.

Even though I knew prior to this that a defendant does not have to testify in court, I did not know why. Luckily (for me?) the judge told us briefly about the history of this rule. For those of you who do not know, a defendant does not have to testify because forcing a defendant to testify is akin to torture. In England during the 15^th to 17^th centuries, courts would determine guilt by torturing victims until they made a statement. This practice was abolished in the 18^th century, and defendants no longer had to answer questions. This rule was incorporated into US law with the adoption of the Fifth Amendment. (Another random fact I learned from the judge- in the US, judges did not wear formal robes until the 1880s- the history of this dress code formality can be found here).

Last, I was quite amused at the behavior of the last group of potential jurors. Some background- the day began with the first group of 14 potential jurors (they eventually needed 12 regular jurors and 2 alternates). They chose 5 people from this group (I was in this group, probably because I am unlucky, but I digress!). Then there was the second group of jurors, in which 6 people were picked, which brought the total to 11 jurors, with 3 slots left. Then there was the third group of 14 jurors, in which 3 people would be chosen. The judge indicated that the first 7 people in this group were more likely to be called as jurors than the second 7 people. Apparently instead of looking at the entire group of 14 as a whole to determine who would be jurors, the judge, prosecutor, and defense attorney looked at each juror, in the order they were selected, and determined if they would be a juror or not.

So, out of all the potential jurors questioned that day, these 7 potential jurors had the highest probability of being selected compared to all the other potential jurors. If these people really did not want to serve on a jury, they really had to put in the effort to be sent home. In addition, these potential jurors had more information about what would disqualify them as jurors, as they were able to observe how the other 28 potential jurors acted, observe which ones were sent home, and then make inferences based on this information what they had to do to be sent home. As expected, as the judge, prosecutor, and defense attorney asked these 7 potential jurors questions one by one, most of them made unusually inflammatory statements about how they could not be fair and impartial in the trial. I found this slightly amusing (cynical me again). The judge, prosecutor, and defense attorney ended up having to select potential juror 8 as an alternate since 5 of the first 7 jurors disqualified themselves. If the potential jurors in the first two groups acted this way earlier in the day, I imagine the judge would have had to call a fourth group of potential jurors because there would not have been enough people to fill 14 slots.

The Trial

Before the trial began, the judge instructed us to base our decisions on the law and to not make our decisions based on what we think the law should be. In his words, we were not able to legislate. Nevertheless, even though were not able to legislate, it is clear to me now that sometimes when legislators pass laws, they delegate some power to judges, lawyers, and jurors to interpret the laws they write.

Background- The defendant of the case, Grant Ackley, is a Level 3 sex offender. In New York State, all Level 3 sex offenders have to fill out a form with a county or state government office that states their current residence every 90 days. They also have to bring in a letter they received at that address within 10 days of the application to prove they are living there. In addition, if a Level 3 sex offender moves within the 90 day period between applications, they have 10 calendar days to report their move to a county or state government. On December 14, 2011, Grant Ackley filled out a form indicating he was living at the Woodridge Hotel in Canandaigua, NY. He did not provide the proper mail to prove his residence, but the clerk accepted his application anyways. On the same day, he also filled out a form for food stamp benefits stating the same address.

There were three charges in the case: (1) the prosecution claimed that Grant Ackley moved out of the Woodridge Hotel sometime in October 2011, he moved into an apartment of a friend who lived above a toy store, and he failed to inform a county or state government official of his move within 10 days of his move; (2) he falsely filled out his 90 residence form with a fake address; and (3) that he also falsely filled out a food stamps application with a fake address. As a jury, we had to determine what a residence or address really meant, and determine whether Ackley gave his correct residence or address. In other words, instead of the legislature or the bureaucracy determining what a residence or address was, it was the responsibility of the jury to determine this definition.

The trial itself only lasted 2 days. Nevertheless, the prosecution presented a lot of evidence on the first day and it was mentally exhausting. I am glad we were able to go home around 4 pm on that day, as it gave us all the opportunity to process the information.  

Jury Deliberations

Jury deliberations lasted about 4 hours. Every one of the jurors was polite and open to having an honest/ educated debate, so it was a pleasant experience. I really enjoyed working with them. I feel as though we examined the evidence differently than the prosecutor and defense attorney. Although both lawyers connected some of the dots for us, it was really up to us to examine the evidence to find proof beyond a reasonable doubt that the defendant was guilty.

How we decided: We found the defendant guilty on all 3 charges.

How I came to my conclusions:

(1) Based on the evidence presented, it is clear that at some point prior to October 2011, Grant Ackley lived at the Woodridge Hotel. Nevertheless, it is pretty clear that he moved out sometime at the end of October/ beginning of November. He was unable to live at the hotel because he could not pay rent. His income was too low. He would have had 5 dollars left to his name every month if he lived there for an entire month at a time. In addition, back in October, he already owed the hotel back about 250 dollars back rent. One of the witnesses from the hotel testified that he still has not paid his back rent. So by the end of October, he was financially unable to live at the hotel, as his income would have been unable to cover the rent plus the back rent. (2) In addition, he also did not pick up his mail from the Woodridge Hotel, his purported mailing address. The prosecution provided evidence of returned mail from the hotel that indicated Ackley was not there for at least 15 days in November. (3) It was pretty clear throughout the trial that Grant Ackley spent a great deal of time at his friend’s apartment during the months of October, November, and December 2011. He also had a lot of belongings at that apartment. (4) The prosecution also provided 2 pieces of evidence where the defendant stated that his address was his friend’s address, not the Woodridge Hotel. During a 911 call about a domestic dispute, Ackley identified his friend’s address as him own. In addition, when Ackley was arrested on December 31, 2011, he identified his friend’s address as his own. (5) The hotel worker provided evidence that someone else was occupying the Woodridge Hotel room from December 22 to December 28, 2011. Ackley could not have lived there. Even IF Ackley lived at the hotel until December 21, based on the law, he would have had to report this move by December 30, the last calendar day he was able to report, which he did not. (6) Last, the evidence definitely suggested that Ackley was not living in the hotel in November and at the end of December. Could Ackley have paid 400 dollars to stay at the hotel in the middle of December to stay there for the week of December 14, 2011? Maybe, but that would have been half his monthly income and he had no intent on staying there long term. His permanent residence was with his friend, as indicated by him being there after December 21, 2011. Essentially his stay at the hotel would have been considered a short vacation or trip, only a temporary movement.

Final Thoughts

As I stated earlier, I am glad I participated on a jury. I am now less cynical about the judicial process. I can also share this experience with my students in the future. Maybe I can leave them with a more positive view of the US judicial system. In addition, after this experience, I feel like I should participate more in politics and other government related activities. It was fun to analyze the judicial process. But I also feel like I learned a lot too, about a topic that is relevant our discipline.

And, finally, just for fun:

Kudos to those who get the reference!