Empirical Implications of Theoretical Models at U-M: Advancing Political Science through Integrated Training
Why EITM Matters
The scientific study of politics and social dynamics requires extensive interaction between theoretical models and empirical research. Political scientists often use “formal models” of how people act, make decisions, or influence each other: They translate ideas into equations, diagrams, or structured logic so that they can then understand and predict how political actors relate and behave. But these theories only “work” when they are grounded in empirical knowledge. And vice versa: Empirical results may seem to yield clear implications, but we need strong, well-specified theories to ground interpretative claims.
In short, many gaps persist between theory and empirical research in Political Science.
EITM’s 2025 participants gather around EITM PI Christopher Fariss of the Center for Political Studies, wearing Hawaiian shirts and tropical looks in his honor.
For more than 20 years, the Empirical Implications of Theoretical Models (EITM) Institute has gathered cohorts of early-career scholars for an intensive, interdisciplinary summer course that gives participants opportunities to explore innovative research practices linking theoretical models with empirical data.
Hosted by Center for Political Studies at the University of Michigan Institute for Social Research, and funded by the National Science Foundation, EITM’s two-week program is designed to immerse students in the rigorous art of bridging logic and data. Through lectures, workshops, and collaborative projects, participants learn new tools and ways of thinking about their research in fundamentally richer ways.
The EITM Summer Institute offers younger scholars an opportunity to obtain such skills by working with senior scholars who are leaders in advancing theoretical and empirical research. Program participants advance their own research by employing their newly gained knowledge about the integration of theory and method into their own research designs, and in working together, build a lasting network of scholars and collaborators.
Learning to Build and Test
EITM doesn’t just teach formal modeling or empirical analysis: it’s about integration, and participants spend their two weeks building a tool-kit for approaching their research questions.
Nguyen Ha, a 2025 EITM participant who is a fifth-year PhD candidate at Vanderbilt, spoke of the value of working with others with many different approaches and substantive focuses. “I learned there isn’t only one way to test game theory implications,” said Ha. “Getting a broad set of options from multiple people was really valuable.”
The Center for Political Studies spoke with 19 scholars about their experiences participating in the 2025 EITM program.
Numerous students praised sessions on structural topic modeling, large language models (LLMs), and computational methods, noting that these are rapidly becoming essential tools for modern research. Brandon Stewart’s session on text analysis was cited as “particularly important,” helping students bridge theory with empirical patterns in vast textual datasets.
The Institute fosters pluralistic thinking, exposing students to multiple methods, approaches, and best practices across diverse subfields, from American politics to international relations.
For some, this meant grappling with quantitative models for the first time (“I didn’t know much, almost at all, about formal models,” one empirical researcher shared), while for others, it was about deepening their understanding of how theory can inform and be informed by real-world data.
Small-group projects mix teams of empiricists and theorists, fostering cross-pollination and broadening participants’ perspectives.
These exercises honed research skills and forged new collaborative bonds. More than one participant is currently co-authoring papers with their EITM teammates, preparing for presentations at major political science conferences.
Building a Scholarly Community (Even / Especially in Saline)
Beyond methods, EITM is also about mentoring, networking, and professional development.
Participants from the 2025 EITM program highlighted the value of direct, personalized feedback from faculty mentors and visiting speakers, describing how these interactions shaped their dissertation projects, job market papers, and future agendas.
“From all the programs I have attended, this was probably the most beneficial in terms of methods and professionalization,” one respondent summarized, noting that EITM provided advice not only about research, but about job market preparation and career-building. These informal discussions—whether at office hours or late-night group sessions—were “where the real meat was.” They yielded insights and friendships that lasted beyond the two-week workshop.
The 2025 EITM workshop happened to coincide with the United Association of Plumbers and Pipefitters training program that fills hotels every August in Ann Arbor. (The location of this convention in Ann Arbor is in fact historically linked to evaluation research conducted by the Research Center for Group Dynamics at the Institute for Social Research.) The logistical hiccup of limited space landed EITM attendees at a hotel outside Ann Arbor last summer– and though it meant less time in town, the downtime in Saline was really beneficial for fostering friendships and collaborations.
Whether in working groups, hotel lobbies, or group dinners, the environment encouraged sustained collaboration and mutual support. As Dot Sawler put it, “the depth of [these] connections… are a function of that intensity.”
The result? Long-lasting networks, a WhatsApp group still buzzing months later, and a community that makes national conferences feel a little less daunting—a kind of “summer camp for nerds,” as one participant put it.
Intellectual Confidence and Community
Ultimately, EITM’s value lies not just in the methodologies learned, but in the confidence gained and the friendships forged. As Lin Xu reflected, “EITM fostered a community of collaboration, not just about methods or models—it’s about building a common language between theorists and empiricists.”
Political science today faces new frontiers—from evolving methods to urgent societal questions. Since 2002, EITM has offered intensive, integrated, and communal training to foster the next generation of scholars.
What advice would EITM students give to future or prospective trainees?
“If you get the chance, do it. You’ll grow as a researcher—and leave with lasting connections.”
EITM may not convene in 2026, but will run future sessions if funding allows. Tevah Platt, Laiyla Santillan, Julia Lippman, and Lauren Guggenheim, all staff of the Center for Political Studies, contributed to the development of this post.
Explore the University of Michigan’s Center for Political Studies:CPS
National Science Foundation Grant #SES-2033912
PIs of EITM include Christopher Fariss, Monika Nalepa, Tara Slough, Rocio Titiunik, and Scott Tyson.
EITM Instructors include Tara Slough, Scott Tyson, Monika Nalepa, Zhaotian Luo, Bobby Gulotty, Maggie Penn, John Patty, Brandon Stewart, Emily Sellars, and Chris Fariss.
EITM Mentors in Residence include Zuheir Desai, Maria Silfa, Cesi Cruz, Kenneth Lowande, Iain Osgood, Deborah Beim, Yuki Shiraito, Tyler Simko, and Ji Yeon Hong.
Housed in the Center for Political Studies at the Institute for Social Research, The Constituency-Level Elections Archive(CLEA) is a repository of detailed results from lower and upper house elections fromaround the world. The project provides opportunities for students to be involved at all stages of the data collection process, providing a valuable training experience.
Brooke Booska, an undergraduate sophomore studying economics and philosophy, joined the CLEA team as a research assistant in September 2022.
“I was hoping to gain research experience and especially to work on something that feels more impactful than an academic assignment,” she said. “CLEA offered me the opportunity to expand my role at U-M from being a student to being a part of something serving the greater public.”
At CLEA, Booska uses a source and a template to code election data and input results into a CLEA-formatted spreadsheet that contains a rich set of information about candidates, parties, awarded vote proportions, and seats won. Booska said it can take anywhere from a week to several months to code an election for CLEA, depending on the voting system size.
Booksa shared three benefits of her work on CLEA:
Learning about different electoral systems in different countries
Getting to know students and faculty outside of her regular circle, with a fun and welcoming team
Gaining transferable skills in Excel and project and task management
“From working on CLEA, I have learned how to tackle large projects. When you are entering data for an enormous country like Canada, it can seem daunting and never-ending,” she said. “Yet, if you can learn to break up the task into smaller, more achievable ones, the overwhelming project becomes much more manageable. This method for working on large tasks has trickled into my school work, especially essay writing. Instead of avoiding intimidating assignments, I have learned to bend them in such a way that works for me. This has made me much more comfortable tackling larger projects and goals such as studying abroad.”
More than 80 students have participated in CLEA, many of them through the Undergraduate Student Research Opportunity Program (UROP). Participation has shaped many of their research interests and career paths.
For the past two years, a team of data science experts have been experimenting with offering expert office hours to facilitate the adoption of new methods and technologies across the Institute for Social Research (ISR). These CoderSpaces provide immediate research support and offer hands-on learning opportunities for participants who wish to grow their coding and data science skills. The aim is to foster a casual learning and consulting environment that welcomes everyone regardless of skill level.
CoderSpaces are one way to help researchers thrive in an environment that is becoming increasingly complex. With the ongoing digitization of our daily lives, scholars are gaining access to new types of data streams that have not been traditionally available in their disciplines. For example, social scientists in the ISR at the University of Michigan have started to explore the ways in which virtual interactions on social media platforms can inform the scientific inquiry of socio-behavioral phenomena spanning many aspects of our lives, including election forensics, political communication, parenting, or insights gained from survey research.
Processing and analyzing novel types and ever bigger quantities of data requires that faculty, research staff, and students incorporate new research technologies and methodologies in their scientific toolkits. For example, researchers may need to move computationally intense analyses to a high performance computing cluster, which requires familiarity with batch processing, a command line interface, and advanced data storage solutions. Or researchers may be confronted with understanding and implementing natural language processing and machine learning to systematically retrieve information from large amounts of unstructured text.
Researchers who embark on the journey of exploring new technologies or methodology often can not fall back on curricula and training opportunities provided by their disciplinary peers. The relevant learning resources still need to be developed – potentially by themselves one day. To bridge training gaps, scholars look to example applications in other disciplines, engage in interdisciplinary research collaborations to access necessary expertise, and solicit help from available support units on campus to make methodological and technological innovations possible.
CoderSpaces provide just this kind of support. The sessions are hosted by faculty, research staff, and students who are willing to share their methodological and programming expertise with others. Initially, CoderSpaces were limited to the ISR community. Currently, anyone at the University of Michigan is welcomed to join, which has allowed us to diversify and broaden the available expertise and research applications. The weekly sessions were originally organized as in-person gatherings at the ISR with the intent to venture out to other campus locations. In March 2020, CoderSpaces moved to a virtual format facilitated by Zoom video-conferencing and a Slack communication space. Going virtual turned out to be a blessing in disguise as it enabled anyone at the university to participate regardless of their physical location, helping us broaden our reach across U-M departments and disciplines.
We have continuously increased the number of our CoderSpaces hosts over time. The current Winter 2021 team is our largest and most diverse yet, with 16 hosts representing nine campus departments that span the social and medical sciences, technical and statistical fields. The expertise we are able to provide ranges from high performance and parallel computing, cloud analytics, performance analysis, statistical modelling and machine learning, survey methods, natural language processing, research design, reproducible workflows, data management, programming in a variety of languages (bash, C, C++, C#, CMake/GNU Make, Fortran, Java, Javascript, Julia, LaTeX, Matlab, Markdown, Perl, Python, R, Rcpp, SAS, shell, Slurm, SQL, Stata), version control in Git, mobile app development, web scraping, and more. Typically, we are able to assist participants with their issues immediately during the virtual meeting. If a solution is not readily available, our hosts draw on their respective expertise and network to identify additional resources and offer support.
Participants join an ongoing Zoom meeting at the scheduled weekly times. The hosts on the call field questions and may use the breakout room feature to assist multiple participants simultaneously. For example, Bryan Kinzer, a PhD student in Mechanical Engineering, attended CoderSpaces a few times to set up and run a Singularity container. He says of his experience: “The hosts were helpful and patient. My issue was not a super easy quick fix, but they were able to point me in the right direction eventually getting the issue resolved. When I came back the following week they remembered my case and were able to pick right back up where I left off.”
Paul Schulz, a senior consulting statistician and data scientist for ISR’s Population Dynamics and Health Program (PDHP), has now been serving as a host since the CoderSpaces were launched. He describes the weekly CoderSpaces as “an enriching experience that has allowed me and the other PDHP staff members to socialize and broaden our network among other people on campus who work in the data and technical space. By sharing our technical skills and knowledge with attendees, we are providing a service. But we have also been able to improve our own skills and expertise in these areas by being exposed to what others across campus are doing. By fostering these types of informal collaborations and shared experiences, I think that the CoderSpaces have been a win-win for both attendees and hosts alike.”
Perspective on research from Guoer Liu, doctoral student in Political Science, and recipient of the 2019 Roy Pierce Award
Guoer Liu
“Not which ones, but how many” is a phrase used in list experiments instruction, where researchers instruct participants, “After I read all four (five) statements, just tell me how many of them upset you. I don’t want to know which ones, just how many.” In retrospect, I was surprised to see that this phrase encapsulates not only the key research idea, but also my fieldwork adventure: not which plans could go awry, but how many. The fieldwork experience could be frustrating at times, but it has led me to uncharted terrain and brought insights into the research contexts. The valuable exposure would not have been possible without support from the Roy Pierce Award and guidance from Professor Yuki Shiraito.
Research that I conducted with Yuki Shiraito explores the effect of behavior on political attitudes in authoritarian contexts to answer the question: does voting for autocracy reinforce individual regime support? To answer this question, two conditions need to be true. First, people need to honestly report their level of support before- and after- voting in authoritarian elections. Second, voting behavior needs to be random. Neither situation is probable in illiberal autocracies. Our project addresses these methodological challenges by conducting a field experiment that combines a list experiment and a randomized encouragement design in China.
In this study, list experiments are used instead of direct questions to measure the respondents’ attitudes towards the regime in the pre- and post-election surveys. The list experiment is a survey technique to mitigate preference falsification by respondents. Although the true preference of individual respondents will be hidden, the technique allows us to identify the average level of support for the regime within a group of respondents. In addition, we employ a randomized encouragement design where get-out-the-vote messages are randomly assigned, which help us estimate the average causal effect of a treatment. For effect moderated by prior support for the regime, we estimate the probability of the prior support using individual characteristics and then estimate the effect for the prior supporters via a latent variable model.
While the theoretical part of the project went smoothly and the simulation results were promising, the complication of fieldwork exceeded my expectation. For the list experiment survey, the usually reticent respondents started asking questions about the list questions immediately after the questionnaires were distributed. Their queries took the form of “I am upset by option 1, 2, and 4, so what number should I write down here?” This was not supposed to happen. List experiments are developed to conceal individual respondents’ answers from researchers. By replacing the questions of “which ones” with the question of “how many,” respondents’ true preference is not directly observable, which makes it easier for them to answer sensitive questions honestly. Respondents’ eagerness to tell me their options directly defeats the purpose of this design. Later I learned from other researchers that the problem I encountered was common in list experiment implementation regardless of research contexts and types of respondents.
The rationale behind respondents’ desire to share their individual options despite being given a chance to hide them is thought-provoking. Is it because of the cognitive burden of answering a list question, which is not a familiar type of questions to respondents? Or is it because the sensitive items, despite careful construction, raise the alarm? Respondents are eager to specify their stance on each option and identify themselves as regime supporters: they do not leave any room for misinterpretation. To ease the potential cognitive burden, we will try a new way to implement the list experiment in a similar project on preference falsification in Japan. We are looking forward to seeing if it improves respondents’ comprehension of the list question setup. The second explanation is more concerning, however. It suggests the scope condition of list experiments as a valid tool to elicit truthful answers from respondents. Other more implicit tools, such as endorsement experiments, may be appropriate in those contexts to gauge respondent’s preference.
Besides the intricacies of the list experiment, carrying out encouragement design on the ground is challenging. We had to modify the behavioral intervention to adapt needs from our local collaborators, and the realized sample size was only a fraction of the negotiated size initially. Despite the compromises, the implementation is imbued with uncertainty: meetings were postponed or rescheduled last minutes, instructions from local partners are sometimes inconsistent and conflictual. The frustration was certainly real. But the pain makes me cognizant of judgment calls researchers have to make in the backstage. The amount of effort required to produce reliable data is admirable. And as a consumer of data, I should always interpret data with great caution.
While the pilot study does not lead to a significant finding directly, the research experience and the methods we developed have informed the design of a larger project that we are currently doing in Japan.
I always thought of doing research as establishing a series of logical steps between a question and an answer. Before I departed for the pilot study, I made a detailed timeline for the project with color-coded tasks, flourish-shaped arrows pointing at milestones of the upcoming fieldwork. When I presented this plan to Professor Shiraito, he smiled and told me that “when doing research, it is generally helpful to think of the world in two ways: the ideal world and the real world. You should be prepared for both.” Wise words. Because of this, I am grateful for the Roy Pierce Award for offering the opportunity to catch a glimpse of the real world. And I am indebted to Professor Shiraito for helping me see the potential of attaining the ideal world with intelligence and appropriate tools.
Post developed by Mara Ostfeld and Catherine Allen-West
The effectiveness of America’s system of democratic representation, in practice, turns on broad participation. Yet only about 60 percent of voting eligible Americans cast their vote in presidential elections. This number is nearly cut in half in off-year elections (about 36 percent), and participation in local elections is even lower. This lack of electoral engagement does not fall equally across racial and ethnic subgroups. Latinos, for one, are particularly underrepresented at polling booths across the country. In 2016, eligible Latino voters were about 20 percentage points less likely to vote than their White counterparts, and about 13 percentage points less likely to vote than their Black counterparts.
This fall, a group of 24 University of Michigan undergraduate students sought to explore this disparity and pinpoint what, if anything, works to increase Latino political participation. In the class, entitled The Politics of Latinidad, CPS Faculty Associate and U-M Political Science ProfessorMara Ostfeld taught her students how to measure public opinion and challenged them to analyze the factors that affect Latino political participation.
Today, more than 50,000 Latinos live in Detroit and a majority of them reside in City Council District 6 in Southwest Detroit which is precisely where this course focused. The students began by studying the history of Latinos in Southeast Michigan and exploring how Latinos played critical roles in the city’s development dating back to before World War I. They analyzed broad trends in Latino public opinion, and considered how and why these patterns might be similar or different in Detroit. Students then designed their own pre-election polls to take into the field.
In order to understand what affects voter turnout, students surveyed over 300 residents of Southwest Detroit to measure the issues that were most important to them.
Students pictured here: Storm Boehlke, Mohamad Zawahra, Alex Tabet , Hannel So, Sion Lee.
The results illustrate some powerful patterns. Among the issues that the residents found most important, immigration and crime stood out. Forty-nine and 45 percent of Latinos listed immigration and crime, respectively, as issues of particular concern, with only 31 percent of residents saying that they felt safe in their own home.
Latinos in Southwest Detroit feel extremely high levels of discrimination. Seventy percent of Latinos surveyed said they felt Latinos face “a great deal” of discrimination. This significantly exceeds the roughly half of Latinos nationwide who say they have experienced discrimination.
Student Alex Garcia visits residents in Detroit.
Local issues were also at the forefront of residents’ minds. Latinos had mixed views on the city’s use of blight tickets to combat housing code violations, with one third of respondents supporting them and one third opposing them.
As local organizations, like Michigan United, continue trying to get a paid sick leave initiative on the ballot in 2018, they can expect strong support among Latinos in Southwest Detroit. About two out of every three Latinos in the area indicated they would be more likely to support a candidate who supports the paid sick leave requirement.
The students then followed up with the residents a month later to see if they planned to vote in the upcoming city council election. At this point, the students implemented some interventions that have been used to increase political participation like, evoking emotions that have been shown to have a mobilizing effect, framing voting as an important social norm, and speaking with voters immediately before an election. With the election now over, students are back in the classroom analyzing the effectiveness of these interventions and will use their first-hand experience to better understand public opinion and political participation.
As an undergraduate student at the University of Michigan, Xhensila (Janie) Valencia was interested in participating in the University’s Undergraduate Student Research Opportunity Program (UROP). Through the program, she sought a research project that would allow her to build work experience. “I interviewed for several interesting projects, but CLEA fit best with my majors in political science and international studies and sounded the most promising in terms translating into work skills,” she says. She could not have guessed at the time how helpful CLEA would be in that regard.
CLEA is a repository of detailed results from lower house elections from around the world. CLEA provides opportunities for students to be involved at all stages of the data collection process, providing valuable experience and training for them. Working on research projects can be an excellent way for students to explore whether they would like to further their career in research and academia. Many of CLEA’s alumni have gone on to attend graduate school and obtain research-oriented jobs.
Janie remembers her most interesting work with CLEA data: “I’m originally from Albania and immigrated to Michigan with my family at the age of 5, so when I saw that there was a data file on Albania, I immediately volunteered for it” she says. Because she is fluent in Albanian, and is familiar with its political history, she found that file interesting and easier to work with than some of the others, specifically because she could recognize the names of parties in both English and Albanian without having to overcome some of the usual language barriers that sometimes arise when working with the data.
She also found that focusing on the data from specific countries allowed her to learn interesting things about the political history and mood of a country. In particular, Poland stood out to her because they went from having few parties after the fall of communism to many parties, including the Beer Lover’s Party, whose platform was to promote cultural beer drinking in the country.
Janie credits her work with CLEA for helping her land an internship in the U.S. Senate, and later a job at a company called Congressional Quarterly / Roll Call, a subsidiary of the Economist Group that provides congressional research and reporting to subscribers. She was told that it was specifically her work with CLEA that made her uniquely qualified for the researcher position right out of college. She had been working there for about a year and a half when an opportunity arose for a new position that would allow her not only to work with data, but also to broaden her experiences to interpret the data and write about her results.
Currently, she works at Huffington Post as an editor for a team called HuffPost Pollster where she participates in tracking and aggregating political polls in the U.S., including all the races leading to the 2016 election. She writes articles based on poll results and contributes to a weekly polling newsletter. She believes her CLEA training also helped her attain this job.
Janie sees many parallels between her current position and her work with CLEA. “I think it’s vital to provide free accessible information about elections and public opinion for both research purposes and the public good.” She has allowed the notion to carry her into her current job. “Being able to contribute in a way that makes information accessible to the public, is what I do now, and it is also one of the great things about CLEA,” she added. Being cited by news outlets for her research is both exciting for her and satisfying because it means that the public is directly benefiting from data she helped collect and analyze.
![From all the programs I have attended so far, it was probably one of the most beneficial ones, both in terms of methods and also in terms of professionalization. It was not [just thinking about] theoretical and empirical modeling...but also about how to approach the job market, how to think about publishing, how to think about collaborations. All these other layers played a role in helping me feel better prepared for the job market. -Dagmar Heintze, EITM Summer Program Participant](https://cpsblog.isr.umich.edu/wp-content/uploads/2026/03/Screenshot-2026-03-16-at-8.49.01-AM-1024x575.png)
