Elections in the Silo

This guest post is by Francesco Navarrini, who teaches Introduction to Political Science and European Union Negotiation at the bachelor’s level in European Studies at the University of Coimbra in Portugal. He also lectures on Professional Skills in the Master’s program for European Studies at the same university and at the LLM in Global Food Law program at the University of Parma. Additionally, he is a tutor and project supervisor for the Master’s program in Technology and Public Policy at the International Labour Organization’s Training Centre in Turin, Italy. His research interests focus on the intersection of technology and political science, particularly how Generative Intelligence influences the way users retrieve political information and how this, in turn, may inform their political decisions. Francesco has completed GPTZero’s course on Teaching Responsibly with AI. If you would like to reach out to Francesco, you can find him on his LinkedIn page.

I love using literature to explore political science and explain concepts that might otherwise seem too technical or abstract. For example, last week we discussed cleavages (social divisions), and I introduced Rokkan’s classic theory: how cleavages form, how they become entrenched, and how parties historically exploit them by asking voters to align along overlapping divisions.

We arrived at this topic after an exercise on electoral systems, where I asked the class to split into groups and analyze the pros and cons of different systems. We imagined a country called Pluravia, marked by multiple social fractures (class, ethnic, religious, and so on), where an electoral reform was ongoing. Students were divided into groups and each one should advocate for a different electoral system (proportional, plurality or majority) as the best for this situation. Since many students found the historical explanation of cleavage formation too theoretical, I decided to design an active learning exercise to help them see, in practice, how politicians exploit cleavages to sway voters in their favor, and how this later intersects with sincere or strategic voting, a key lesson from studying electoral systems.

I drew inspiration from Hugh Howey’s Silo trilogy (and the series on Apple TV) to create this exercise. After a brief five-minute introduction (explaining the Silo’s rules and its main social divisions), I divided the class of 40 into four groups of 10. Each group represented one of the Silo’s social classes: Up Top, Mid Rangers, Lower Mids, and Down Deep.

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Inquiring Minds are Engaged Minds: Exit Polling as an Active Learning Exercise

Today’s guest post comes from Dr. Justin Crofoot (Penn State University, PA) and  Dr. Rolfe Peterson (Susquehanna University, PA)!


In the Fall 2024 semester, students from 11 different universities across Pennsylvania (including ours: Penn State and Susquehanna University) conducted exit poll surveys for the presidential election. Each university independently organized their students and sent them to precincts to survey voters regarding their vote choice, policy preferences, and other important issues. This active learning project gave students the opportunity to gain real-world experience, insight into the electoral process, and practice analyzing survey data. Below we discuss the preparation, the exercise, and the pedagogical use during and after.

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A post-election conversation with our students: a suggestion

I am writing this post more so as a brief reflection about how I approached speaking to my classes today (11/6) after the results of the US presidential (any many other) elections. This post may be rough and brief, but I think for those of you who are teaching Political Science (broadly) or engaging with your students in some capacity today or in the next few days about the US election, this might be interesting to consider. This post might not be relevant anymore next week – or it could help in general facilitate a conversation about any “touchy” current issues that we feel necessary to clue our students into.

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Media literacy in political science education

2024 has been labelled a ‘historic year for democracy’ as around 1.5 billion people go to the polls in elections in more than 50 countries. Whilst the US election is likely consuming a lot of our attention and the bulk of newspaper space, between now and 5th November there are also elections in Austria, Czechia, Sri Lanka, Georgia, Mozambique, Uruguay, Jordan, Tunisia, and Botswana.

At the same time as this boom year for elections, there is growing concern about how misinformation, accelerated by the use and capabilities of generative AI, might be impacting political engagement. The risk of generative AI disrupting voters’ behaviour is something that is already being seen – in January AI-generated messages, claiming to be from Joe Biden, urged voters in New Hampshire to not vote in the state’s primary election for the Democratic Party. 

Of course, misinformation and ‘fake news’ is nothing new. Research into Twitter usage during the 2016 US presidential election found that in the five months before polling day a quarter of tweets sharing news links contained either fake or extremely biassed information. What is clear is that this is a problem that is not going away. It is also clear, as well articulated by Jonathan Parker in a Journal of Political Science Education article earlier this year, that the post-truth era poses a challenge for Higher Education. 

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Electoral Simulators

A brief post for today — I’m still recuperating from removing half a meter of snow from the sidewalks and driveway after the Blizzard of 2022.

For people who teach voting and elections as part of comparative politics:

The New York Times recently published Hexapolis, a gerrymandering game, on its website. The accompanying example of Austin, Texas, is useful.

Another great tool is Nick Case’s interactive simulation of different voting systems, To Build A Better Ballot.

Teaching Election Results

The 2018 midterm elections are over in the US, and it was a night of mixed results.  The Democratic Party took control of the House of Representatives, winning at least 27 seats previously held by the Republican Party, while the GOP increased their majority in the Senate, toppling North Dakota’s Heidi Heitkamp and my own state of Missouri’s Claire McCaskill.  

While clearly not as momentous an election as 2016, or the Brexit referendum, or many other elections, the midterms were still an important point to take stock of the impact of Trumpism on American politics, and whether Democrats who were somewhat over-confident in the fall of 2016 could manage to overcome pro-Trump sentiment, a strong economy, congressional district gerrymandering, voter suppression efforts, and the other structural reasons why succeeding at the polls can be difficult. 

Teaching the results of American elections is a frustrating enterprise.

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Electoral College Exercise

While I realize many of our readers are not based in the US nor teaching American government, the Electoral College is such an interesting oddity in electoral decision making that its a subject that may come up in Comparative Politics courses as well.  Certainly when I teach US politics I use quite a few comparative examples, as one of my themes of the course is how government arises from a series of decisions made by individuals and groups, none of which are or were set in stone.  Showing alternative models is a very useful way of doing this.

So here is a data analysis exercise that I use to teach the American Electoral College. It can be done either as homework or as an-in class as an activity after a basic introduction to the Electoral College and how it works (the basic premise of state-by-state popular vote, proportional votes based on number of seats in Congress, winner take all systems, and if no one wins a majority, the decision is made by the House with state-by-state voting).  

This exercise can be easily reformed for a final exam. Simply change the data and situations.  In the version below I use 9 states in a fictional world; in the exam version, I use about 20 states in a different world.  I never use the entire US or actual vote totals–this is largely to keep the math simple enough that it is not a test of arithmetic but of analysis.  Feel free to change the names of candidates and states to suit your own interests. 


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An Exercise for Teaching Campaigns and Elections

Today’s post comes courtesy of Dr. Julia Azari, Associate Professor in the Department of Political Science at Marquette University.  Her exercise can be used in American politics classes that include a unit on campaigns and elections.  It can be done in a single class or as a multi-day exercise. These are the instructions she gave to the students, reprinted here in full. Where page numbers are given, they refer to the text used in the class:Matt Grossmann, John Sides, Daron Shaw and Keena Lipsitz, Campaigns and Elections, WW Norton, 3rd Edition.


The scenario: In April 2019 (just a few months from now!), President Donald Trump has once again shaken the political world by announcing that he will not seek reelection to a second term. Citing the decisions of Harry Truman, Lyndon Johnson, James K. Polk, and Rutherford B. Hayes, the 72-year-old entertainer-turned-politician said that he wanted to spend more time with his grandchildren, missed his old life, and was satisfied with his incredibly successful first term.[1]

As a result, we have a 2020 election with no incumbent! After tough primary battles on both sides, in July 2020, Republicans and Democrats are settling in for the general election. And it just so happens that candidates from both major parties are eager to hire consultants who have studied political science at Marquette.

Political conditions: Economic growth is steady and no new wars have begun. Trump’s favorability ratings have improved a bit with his decision not to seek reelection, but have remained around 45%.

Now you have to form a consulting firm (a group with 4-5 classmates) and decide which party’s candidate you are advising.[2] Unfortunately, instead of collecting a handsome fee, your end goal is to turn this sheet into me and get a participation grade for the day.

Here are the decisions you’ll need to advise the candidate about:

  1. Fundraising.

How will you do this? Who will you ask to contribute? Do you want to make promises about your commitment to “clean elections” or resisting a certain kind of contribution?

You can’t coordinate with expenditure-only organizations, but how much are you comfortable with letting them pick up the bulk of the campaign spending? Does their existence give you some breathing room to back off of fundraising in favor of other activities? Can you count on their help? What are some benefits and risks of counting on it?

What kinds of campaign fundraising do you expect from your opponent? How will you respond to attacks from independent expenditure groups?

  • Television ad buys (see page 268). What states/media markets will you focus on? Which states do you consider safe and which will be competitive, but attainable? Will you take a risk on running ads in states where your opponent still has the best chance to win?
  • Travel. Where will you go? How many appearances will you make between Sept. 1 and the election? (See page 269) What are the costs and benefits of this strategy?
  • Messages and priorities. What issues will you emphasize? What will you say about the status quo – knowing what you know about forecasting models? How will you balance your appeals to swing voters and your political base?

[1] Note: I don’t think this is an especially plausible scenario, but I don’t this exercise to be focused on the current president because we have other things we need to discuss.

[2] You can speculate about who your candidate is, but again that’s not really the point of the exercise.

New Gerkhania Simulation

A slightly delayed report on the latest version of my Gerkhania simulation, which I abandoned back in 2015 because it wasn’t living up to expectations. Last January I wrote a brief preview about changes I had made to it before the start of my spring semester comparative politics course.

Gerkhania now has three rounds of role play: a commission to establish a representative legislature, one legislative session in which students can earn points if certain bills are passed, and a third session with no point rewards. For each session, students randomly receive a short biographical profile with an ethno-religious identity. Because of the laws of probability most students will receive a different role each time. The roles also include objectives that students should try to pursue; the objective of one student conflicts with the objectives of most of the other students.

In the first session, the class almost agreed to three separate electoral districts before settling on a single, national district to elect members of a parliament. In the debate, students quickly affiliated with each other on the basis of their newly-assigned identities. The same behavior occurred in the other two sessions, even though students had different identities . Students spontaneously changed seats to sit next to those who had the same ethnicity. They tried to maximize their own group’s influence and marginalize the influence of others. Some students tried to simultaneously engage in logrolling across ethnic boundaries to achieve their individual objectives.

In the post-simulation debriefing, I highlighted two topics. First, the results of both legislative sessions, in terms of passage or failure of the bills I supplied, were nearly identical — despite the existence of a zero-sum environment for earning individual rewards in the first session but not the second. I asked students whether this outcome could be explained by rational actor theory.

Second, I tried to get students to think about the immediacy and fervor with which they adopted rapidly changing and completely arbitrary identities. I say “tried” because I don’t think I was able to get students to adequately connect their behavior during the simulation to concepts like identity salience, deindividuation, and culture. But obviously identity had a much larger effect than it did in my South China Sea simulation, which is what I had intended. So I rate this activity as a success.

All materials needed to run New Gerkhania are available through my TeachersPayTeachers storefront.

Parliament Game with the Gray-Tufted Banderwot

Gray-Tufted Banderwot

A few years ago, Simon invented a game to model coalitions in the European Parliament (also described here and here). I decided to try it in my comparative politics as a lesson in how legislatures function. After some confusion as students figured out what to do, they clustered into two coalitions; the outcome loosely resembled a two-party/median voter system. But I had forgotten to remove the high-value cards from the deck before starting the game. The class has only fourteen students, and the distribution of card values was so great that it was difficult for students to accumulate influence points.

I decided to run the game again in the next class, after removing face cards from the deck. Influence points were calculated the same as before. But I added a twist. Each student received additional instructions that varied according to the value of his or her card: Continue reading “Parliament Game with the Gray-Tufted Banderwot”