Research Assistantships

Summer Institute in Social Research Methods Research Assistant Program

University of Chicago undergraduates enrolled in the annual Summer Institute in Social Research Methods are eligible to participate in the research assistant grant program which  reinforces and extends new research method skills through a faculty-mentored research experience during summer session. Awardees will work as part-time research assistants on an ongoing research project of a Social Sciences faculty member.

It’s been thrilling to accompany the Summer Institute students on a path that starts with the initial first meetings where everything we’re talking about still seems confusing because they’re still new to spatial ways of thinking, methods and computational tools, where everyone makes lots of mistakes and feels awkward and uncertain about the programming, the data, the questions and the methods. As they’re progressing with Marynia’s class and their project, there’s suddenly more traction after digging in and at the end of the summer, they’ve started to acquire a new spatial perspective on research, learned new spatial methods and have made the tools their own in a way that they’re now flying through them confidently. It’s been a beautiful transition to watch. Several of the students got hooked and we’ll be continuing to work with them on funded spatial research projects that will provide them with opportunities to publish a paper, attend a research conference and collaborate with a policy institution. They are now plugging into the larger spatial infrastructure at the Center for Spatial Data Science with our spatial study group, spatial workshops, and a spatial interdisciplinary community. All this is preparing them to be ready for an increasing number of opportunities that are opening up in the computational social sciences.

Julia Koschinsky

Executive Director, Center for Spatial Data Science

2019 Research Projects

Biological Sciences Division

Methods and Analytics Support for Health Services Studies
Students in these assistantships will support data analytics for two research studies. The first study, Comprehensive Care Physician Study (CCP), is an RCT implemented at the University of Chicago Medicine that started in 2012 and was originally funded through the Center for Medicare & Medicaid Innovation’s Health Care Innovation Awards. The study was designed to foster new care delivery models with the three-part aim to create better health, better health care and lower costs. The research assistant will help create real time data quality checks for our data collection tools.

The second project, The University of Chicago Hospitalist Project, is a large clinical research project that targets patients ages 18 and over who were admitted to the general medicine services, and who were able to provide consent or who had a designated proxy. Patient consent was solicited to participate in an interview to collect detailed health and socioeconomic information and contact information for a follow-up telephone interview 1 month after discharge. The research assistant will analyze data from this project that focus specifically on patient preference on receiving care from a hospitalist or non-hospitalist and their willingness-to-pay when cared for by a hospitalist or non-hospitalist; the RA will assist with the data preparation, data manipulation, and statistical analysis of the project.


Automated Economic Reasoning
The social sciences have been profoundly affected by progress in information technology that has facilitated the collection and processing of vast amounts of data related to human activity.  Information technology has so far assisted less with theoretical reasoning of the sort done by Paul Samuelson, Mancur Olson, Gary Becker, James Coleman, or Roger Myerson.  There are automatic algebraic simplifiers, but simplicity is often in the eye of the beholder and such tools are sparingly used by social science theorists.  Computers have already been used for generating numerical examples, but approximation quality is a concern, and more thinking is always needed to appreciate the generality of the results from examples.  These assistantships will work with user-friendly software that, without approximation, automates reasoning in the social sciences.

The Origins and Persistence of Inequality in Denmark
The Center for the Economics of Human Development (CEHD) launched a new initiative aimed at understanding the mechanisms of intergenerational mobility and inequality in the U.S. and Denmark. Analysis is underway using administrative data in Denmark, and we aim to complement this work by utilizing the rich array of public and restricted-use longitudinal survey datasets in the U.S. This assistantship will offer opportunities to

  1. Exploring family and neighborhood mechanisms behind mobility and inequality by:
    • a. conducting comparable counterparts to the team’s a. existing analyses with the Danish data using U.S. survey data, and
    • b. pursuing novel data analysis and extensions to this work that are afforded through this rich survey data;
  2. Working closely with PSID, NLSY, CPS, IPUMS, and/or SIPP datasets to clean and analyze relevant variables for this analysis;
  3. Conducting econometric analyses and generating a variety of plots and visual aids;
  4. Preparing weekly reports and/or presentations for the research team that summarize research findings; and
  5. Assisting both faculty members and graduate students involved in the project in other activities across the research cycle, such as literature reviews, drafting or proofreading new papers or proposals, and replication of results.
Geographical Sciences

Why Spatial Thinking Matters
Many people think spatial analysis means putting dots on a map, i.e. they think of GIS tools and map visualization. However, thinking geospatially about research is much broader as is pertains to the whole research process: From questions to research design to methods and analysis to visualization. At the UChicago’s Center for Spatial Data Science, we collected examples that illustrate how spatial thinking matters in policy-relevant research. These examples highlight insights gained when you apply a spatial perspective compared to traditional non-spatial perspectives on the same research problem. The RA will help present and explain these examples on the CSDS website.

GeoDa Chart Chooser
Spatial analysis courses across the country and world rely on the GeoDa software program to teach exploratory spatial data analysis and spatial regression modeling. Luc Anselin and his team have been developing GeoDa for 20 years. It now has over 280,000 users, with 22k website visitors per month and over 262,000 viewers of Anselin’s spatial analysis courses on YouTube. This research project will add a GeoDa chart chooser to GeoDa’s extensive documentation to help analysts navigate the program’s functionality. Students will gain an overview of spatial analysis functionality during the internship.

Spatial Access Metrics
Much health-related and other research relies on spatial access measures, e.g. to measure spatial access gaps to primary care. However, because it is complicated to compute these measures at scale, there’s a lack of national research that goes beyond the identification of access gaps. For the past 18 months, we have developed the infrastructure to efficiently compute spatial access metrics and travel times between locations at scale. To make this available to researchers and others, we need to write a technical report based on Jupyter notebooks created in Python, which also needs to be updated.

Localization and Co-Location of U.S. Manufacturing and Service Establishments
We will replicate the work of Duranton and Overman, Ellison et al and similar studies using micro-geographic information from the NETS data base, which contains more than 60 million data points. Instead of using distance as the crow flies, we will employ network distance using the U.S. road network computed by means of our new infrastructure. We will assess the sensitivity of the results to the simplifying assumptions necessary to carry out the computations under the current limited technology.

Harris School of Public Policy

The Revolving Door and Talent Allocation: Exploring the Effects of Restrictions on Lobbying Employment on the Labor Supply of Congressional Staff
In September 2007, the Honest Leadership and Open Government Act of 2007 (PL 110-81) was enacted and altered revolving door rules for House and Senate staff making it more difficult for certain staffers to enter careers in lobbying directly after Congressional employment. This legislation could have effects on the labor supply of Congressional staff through two channels: a sunshine channel (removing the perception of corruption) or through the destruction of option value. This paper exploits a natural experiment arising from differential restrictions on lobbying activity of former House and Senate staffers. In doing so, it attempts to uncover any compositional effects limitations on revolving door activity may have on talent allocation.

A Revolution Stalled? The Fate of College Women in the US Labor Market
Female attachment to the labor market increased dramatically from the post-War period through the 1990s slowing post-1990s.  There was a dramatic upskilling of women in the birth cohorts that were driving the increase in participation. Starting with the late 1950s birth cohorts, women overtake men in completion of 4 or more years of post-secondary schooling. Yet, there has been a persistent wedge in compensation between college-educated male and female workers age 35 and older. College women lose the most ground over the life-cycle during the period of likely fertility: ages 25 to 35. In this project, we will use regional variation in the US to better understand the gap in outcomes for college women and college men from the post-War period to present.

My Liberal (Conservative) Neighbor: Effects of Member-to-Member Interactions on Political Behavior within the US House of Representatives
A well-developed literature documents increased polarization within Congress. In an institution in which political silos are deepening, how do Members encounter different policy perspectives? This project asks whether being located next to an ideologically dissimilar office neighbor influences a Member’s political behavior. As social interaction is subject to selection, an empirical challenge arises: How does one test the effects of interaction if members choose their neighbors? Fortunately, the House Office Lottery somewhat randomly assigns office neighbors. This randomization will allow the researcher to test the effect of the interaction induced by office proximity on voting behavior, co-sponsorships, and fundraising.

How Do Electoral Systems Affect Political Campaigns? 
Social scientists have long been interested in the political consequences of electoral systems. In this project, I study how electoral systems affect the organization of political campaigns. I have collected a dataset containing campaign expenditures of all candidates who ran for a seat in Japan’s National Diet from 1965 to 2017. This allows me to measure how candidates organize their political campaigns over time. Over the studied period, Japan has reformed its electoral system several times, and most of these reforms only affected a subset of the seats in the Diet. This will enable analysis of whether the same candidate behaves differently when running under different electoral rules.  More specifically, difference-in-differences design allow analysis of how the same candidate campaigns under different electoral rules (first-past-the-post, closed-list PR, open-list PR and Single-Nontransferable Vote) while differencing out common party-year specific shocks.


Mapping the New Politics of the Global South
This mapping and visualization project seeks to identify the keywords that separate that era of the Third World from that of the Global South. The first stage of the project involves creating a corpus of the yearly speeches given by the world leaders at the United Nations very September from 1950 through 2015 in five year intervals, and preparing them for machine reading.  The second stage involves helping to develop tools for reading the data: identifying frequency of use of keywords over time and between subgroups in the corpus and the affective valences associated with them as well putting together a variety of visual representations including spatial flows of concepts over time.  This is part of a larger research project that combines qualitative and qualitative methods to uncover how new forms political meaning and action are articulated in the imaginary we call the Global South.

Medical Tokyo: Health, Healthcare, and Cityscape
This project makes use of GIS technology to explore the process of medical modernization in Tokyo over the course of the period from 1871-1937. The aim is to explore the relationship of access to health care and material (public transportation, military installations, types of housing, sanitation, etc.) and social aspects of the city (economic class, brothel districts, ethnic enclaves, etc.)  RA applicants should have familiarity with QGIS or ArcGIS.

Fossil Futures: Energy, Growth, and Ideology in Britain 1800-1900
What were the historical origins of the fossil fuel economy, and how did growing awareness of the importance of coal consumption shape the idea of economic growth in political economy, culture, and ideology?

Utopia’s Discontents (History)
I am completing a large-scale historical study of the cultural and political impact of the radical emigration in nineteenth-century Russia. Part of this project has involved GIS and other forms of computational analysis.

Mansueto Institute for Urban Innovation

Array of Things
With a new 100 AoT devices being installed by summer, we will have roughly 200 points of measurement across Chicago, most of which will provide gas measurements (7 different pollutants), weather (temperature, humidity, barometric pressure), sound/noise, and other environmental data such as light.  Additionally, 100 of these units will measure PM1, PM2.5, and PM10.  All units also will be remotely programmable for image and sound analysis, and are currently using image analysis to identify pedestrians and vehicles, providing total number of each at 30s intervals.

Political Science

Domestic Politics and International Relations in South Asia
This early stage of a major project explores how political parties and politicians campaign on (or don’t campaign on) foreign policy issues, and how voters think about these issues, in contemporary South Asia. We know very little about the domestic politics of foreign policy in these countries, yet they include a set of democracies (and semi-democracies) operating in an increasingly complicated international context. Current research has three primary areas of focus: first, measuring the use of foreign policy themes in campaigning, party manifestos, and party-linked publications in India; second, systematically collecting survey results on foreign policy questions in India going back to the 1950s; and, third, gathering data on public opinion and party positions toward China and, where possible, its “Belt and Road” initiative in the smaller states of the region.

Public Support for Declining Industries: The effect of the WARN Act
How does local economic disruption shape support for free trade?  Does the closure of a major employer disrupt or reinforce political support for tariff protection?  Answering this question is difficult because import competition is not randomly assigned or unanticipated.  Communities that fail to adjust are systematically different than those that do not, making inference challenging. In 1988 the US enacted a system forcing businesses to give advanced notice for any action to fire more than 500 employees, the Worker Adjustment Retraining Notification Act (WARN act).  The WARN act offers an opportunity to gain insight into the consequences of public knowledge of economic change and dislocation on politics.  This research project aims to apply the regression discontinuity framework to study the effects of a notification requirement on communities with closures above and below the cutoff for notification.  Moreover, preliminary research has found that state by state laws offer a variety of threshold, allowing for extrapolation away from the effect at the national cutoff. The research assistants will learn about a number of important quantitative methods.  Regarding geospatial analysis, the research assistants will also learn about how to match the geospatial addresses data associated with each facility closure and legislative districts. RAs will also study the effects of these closures on subsequent trade policy responses in the products and industries affected by these layoffs.  This will require the use of econometric approaches and learning about panel and time series techniques. RAs will learn to summarize their findings visually using R and will be mentored by graduate student researchers.

Transitional Justice and Democratic Stability: A New Dataset 1918-2018
We live in an era of democratic backsliding in which fragile new democracies risk reverting back into dictatorship (Bermeo 2016, Lust 2015, Serra 2012). Poland, Hungary, Turkey, and Venezuela (Sedelmeier 2014, Jenne 2012, Cinar 2018, Svolik 2017) reflect an alarming worldwide trend of elected incumbents gradually subverting democracy. This threatens the national security of the United States because the rise of authoritarian states represents a substantial threat to this country and the general global order. Can transitional justice that is, mechanisms established by new democracies to deal with former authoritarian elite prevent sliding back to authoritarianism? Or does such backsliding occur despite extensive transitional justice efforts? To address these issues, my proposed project will 1) develop a comprehensive dataset on how states deal with outgoing autocrats, their collaborators, and perpetrators of human rights violations, 2) identify the theoretical underpinnings of transitional justice, and 3) evaluate the empirical implications of my theory against a novel disaggregated dataset. This research will help policy makers offer and evaluate improved strategies for dealing with authoritarian elites and their collaborators and help consider how new regimes may be guided toward democratic consolidation in the face of potential authoritarian backsliding.

Presidential Daily Brief Project
This project will systematically code a corpus of declassified presidential intelligence summaries delivered daily from 1961 to 1977. Doing so will shed new light on how presidents learn and make decisions, the gap between “insider” and public knowledge, and the relationship between intelligence and policymaking. Presidential Daily Briefs (PDBs) are a fascinating and unique document, providing a candid, granular view of all-source intelligence analysis on the most important national security issues across four American presidencies. Released in 2016 after a special declassification review by the CIA, this project will organize a research team to extract text and other data and code individual PDBs on a number of dimensions to identify changes over time. The researchers will code PDBs for structural features (i.e. variation in length, topics covered, use of redactions) and use automated text analysis tools to identify patterns in the content of intelligence analysis (i.e. variation in predictive vs. reflective analysis, coverage of thematic issues like revolutions vs. military developments). The project will produce a digitized, text-searchable, comprehensive compilation of *daily* PDBs that span 19 years.

In Spring 2019, two RAs did preliminary coding on a subset of the PDBs as well as build out the initial infrastructure for the project (codebook, etc.). I plan several publications drawing on these data but the dataset will also support collaborations with other faculty on campus as well as serving as a public resource for political scientists, historians, and others.  RAs via the summer institute will be instrumental in building the dataset and beginning a first wave of analysis.


Experience sampling/fNIRs
These are two projects for undergraduate research assistants. Each project needs one research assistant.

Project 1: Experience sampling
We collected data for an experience sampling study in which we evaluated participants’ working memory, emotion, and cognition before, during and after they completed the 60-min indoor walk in either an urban or natural environment. A novel technology was created for this study to integrate the experience sampling method with the dual n-back test (a working memory test) on a mobile phone. The goal of this research is to measure cognitive and experience difference before and after exposure to different environments. The data is now available for analysis.

Project 2: fNIRs
Functional near-infrared spectroscopy (fNIRS) uses near-infrared light propagating diffusely through a biological tissue to quantify optical absorption by its main chromophores, essentially hemoglobin species. Measurements at two or more wavelengths enable the characterization of oxy- and deoxyhemoglobin concentrations changes, leading to the determination of changes in blood volume and blood oxygen saturation. The goal of this research is to apply fNIRS methods to measuring and imaging the brain hemodynamic responses under a variety of activation paradigms encompassing notably cognitive and executive functions.

Language Modality and Reasoning Project
Our goal of the project is to understand the relationship between reasoning and language use. People routinely use information communicated via language to reason, pass judgments, and solve problems. This project will investigate how the modality of language – whether it is spoken or written – impacts problem solving and thinking. Specifically, we plan to conduct two studies this summer, the first study examining how language modality impacts how quickly and accurately participants solve problems and the second examining how language modality impacts neural activation through recording event related brain potentials by means of electroencephalography (EEG). In sum, the overall goal of this project is to examine whether receiving information in a different language modality alters the speed and accuracy of problem solving, and to examine the mental processes that underlie these differences.

School of Social Service Administration

Next-Generation Health and Human Services Platform 
This project uses publicly-available data to present a system-wide picture of whether public funds are appropriately matched to identified community needs in cities. This information can help planners and policymakers analyze their financial investments and inform decisions about ongoing spending in a larger context. It uses a set of spatial analytic tools developed by the University’s Center for Spatial Data Science to generate analyses of the spatial match of public funds to needs.

Applications Open November 27, 2019

2019 SISRM Lunch Seminars

2019 Research Assistantship Program

Students in the 2019 RA program

2019 Faculty Mentors

Disciplines represented in research projects

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