Christopher Ansell, Professor

Closed (1) The Post-Socialist European City: Archives in Translation

Applications for fall 2021 are now closed for this project.

**German, Hungarian, or Polish language skills are especially needed**

The European continent has undergone major shifts since the fall of the Berlin Wall. Eleven countries have emerged from a totalitarian Communist system, embracing capitalism and democracy and joining the European Union. These transitions had major effects on governing institutions and practice across the continent. Yet many scholars have found that Socialist legacies endure in spite of major reform efforts, learning initiatives, and aid conditionality. This project seeks to look at the differential legacies of these two major transformations largely in post-Socialist Europe, though will also use comparison cases in Western Europe. While existing research has explored the issue at the national level, this research will focus on subnational variation by looking at the city level.

Students will be responsible for classifying, coding, note-taking, and translating contemporary and historical government documents from German, Polish, and Hungarian sources. German documents tend to be more historical, while Polish and Hungarian data will be more contemporary in nature. The possibility of parallel work for other post-Socialist EU member countries exists if there are students with appropriate language skills. Advanced (Professional to Native) language skills are necessary for participation in this project. The specific tasks will vary by language and skill level, but happy to discuss further with interested applicants.

Students will participate in the project by collecting data from existing government documents and compile research to to explore what makes city governments in Europe more or less effective. Students may also, if they have appropriate language skills, translate media reporting, academic articles, and city plans, beyond the documents already obtained for analysis. German city documents have been collected from city archives and need to be examined and classified and are primarily from the period immediately following the fall of the Berlin Wall. Hungarian or Polish documents will be more contemporary in nature. Hungarian documents will focus on the local aspects of democratic backsliding, while Polish documents will relate to the contemporary judicial system. The project may also extend to research on local political candidates in contemporary Hungary.

This project may be especially appealing to those who are either native speakers of German, Hungarian, or Polish or advanced language majors with a secondary interest in politics. Students will discover the way that European cities fit within the complex multilevel governance of the European Union and the significant ways they vary from one another.

Students will receive hands-on training in data collection and interpreting the relationships and networks, and strengths and weaknesses, of subnational policy making in Europe. They will have experience working with foreign language documents and on translation in a professional environment. Their efforts will significantly inform research that will explore urban policymaking and subnational politics in contemporary Europe. Students will learn about urban and subnational politics in European countries and changes brought by both the post-Socialist transition and admission to the European Union. Beyond substantive areas, students will learn about the early, exploratory stages of large research projects, formulating research questions, and collecting/interpreting data. Supervision will be done remotely with occasional group Zoom meetings, so students must be self-motivated and able to work independently.

Day-to-day supervisor for this project: Matthew Stenberg, Ph.D. candidate

Qualifications: Applicants should have some background and familiarity with European politics. Language skills, especially in German, Polish, and Hungarian, are a requirement. If an applicants has language skills in another post-Socialist EU language, we can discuss possible tasks using those skills; however, we have immediate openings for students proficient in German, Polish, and Hungarian. Please clearly indicate which project you are applying to in your application.

Weekly Hours: to be negotiated

Off-Campus Research Site: remote

Closed (2) Oversight in the European Union

Closed. This professor is continuing with Spring 2021 apprentices on this project; no new apprentices needed for Fall 2021.

The European Union is a complex international organization that influences all aspects of contemporary European politics and society. While scholars have studied how the European Union interacts with nations a great deal, it is often portrayed as having a limited capacity to enforce its rules and norms at the national level in spite of its high-minded ideals. This project aims to look at one key mechanism of oversight in the European Union as conducted by the European Parliament.

*This project is currently closed to new applicants*

For the 2019-20 school year, we are especially interested in having students research, develop, and code datasets relating to the Members of the European Parliament and the European Commission, datasets which will be merged with our other datasets to create a more comprehensive database at project conclusion. For this project (Project 2), no technical expertise is required.

Students will be responsible for researching, coding, and cleaning large datasets pertaining to the European Union's oversight. Subsequent tasks may deal with data analysis using the sets prepared by the students. Additionally, students may be asked to read government documents and either A. take notes, B. code variables, or C. prepare a short memo. These materials may be from contemporary European sources or from historical primary sources, depending on what documents the project can obtain.

Students will discover the way that institutions and oversight work within the complex multilevel governance of the European Union. Students will receive hands-on training in data collection and interpreting the relationships and networks, and strengths and weaknesses, of the relationships between levels of government in Europe. Their efforts will significantly inform research that will explore policymaking and subnational politics in contemporary Europe. Students will learn about national and subnational politics in European countries and changes brought by both the post-Socialist transition and admission to the European Union. Beyond substantive areas, students will learn about the early, exploratory stages of large research projects, formulating research questions, and collecting/interpreting data.

Supervision will be primarily done remotely with occasional group meetings, so students must be self-motivated and able to work independently., Ph.D. candidate

Qualifications: Experience with Excel is required. After the coding phase, which is largely data entry, the complexity of tasks given to students will depend on their technical training -- statistics or more technical backgrounds would be helpful here. Students with interests in European history/government and/or the European Union are also encouraged to apply. Please clearly indicate which project you are applying to in your application.

Weekly Hours: to be negotiated

Closed (3) Quantitative Text Analysis and the European Union

Applications for fall 2021 are now closed for this project.

Parliamentary questions are one of the key means of oversight in the European Union. This project aims to analyze the ways that this oversight process is used at the European level through large scale, quantitative text analysis, machine learning, and statistical methods as well as finalize the data structure for a large N, text dataset that will be made publicly available at the conclusion of the research.

Students will assist with the development of the programs and algorithms needed to analyze the text and to optimize the data structure. This will take the form of coding, largely in python and R, for large scale text analysis and natural language processing. Appropriate levels of technical skills are prerequisites.

We are seeking students for 3 separate sub-projects! Please indicate which project(s) you might be interested in when applying. The first two sub-projects would be interesting to students interested in the early stages of data science work, while the last sub-project would be especially interesting for students interested in continuing real world applications of machine learning and optimization. Possibilities for overlap, and transitioning to another sub-project when one is complete do exist.

1. While we have the first phase of data wrangling done, we have the second phase to go. This involves messy real world data, which must be parsed and reorganized to make usable for text analysis. This will likely involve significant parsing with regular expressions and be heavily reliant on python. The end product is will be a dataset that we will make publicly available.
2. We are working to merge and refine several data sources together, as well as clean the existing and new data sources. This will involve merging multiple data sources, using a variety of techniques to account for inconsistent joining keys and involve designing and structuring data to be used efficiently.
3. We are working to develop and optimize a text classification scheme to assess the presence of Euroskepticism in questions through machine learning. Two preliminary models have been devised, using BERT and Universal Sentence Encoding. We are continuing to optimize the classification scheme, using our training data, to be able to apply it to the remainder of the large data set that is being finalized in subprojects 1 and 2. The tasks for this semester are largely about optimizing machine learning classification models, so experience with optimization, with imbalanced learn methods, and machine learning classification are highly beneficial.

Students will gain experience with developing the tools necessary for large N, quantitative text analysis and hands on experience with designing a dataset of significant size for analysis, as well as practical experience with using programming languages on a real world project. Aspects of the project deal with structural topic modeling, sentiment analysis, machine learning, natural language processing, and statistical methods.

In addition to developing technical skills using real life data, students will discover the way that institutions and oversight work within the complex multilevel governance of the European Union. Students will receive hands-on training in data collection and interpreting the relationships and networks, and strengths and weaknesses, of the relationships between levels of government in Europe. Their efforts will significantly inform research that will explore policymaking in contemporary Europe. Beyond substantive areas, students will learn about both the early and implementation stages of large research projects, formulating research questions, and collecting/interpreting data. , Ph.D. candidate

Qualifications: Please clearly indicate which project you are applying for! Students should be comfortable in python and/or R. Some degree of experience/interest with text analysis or natural language processing would be beneficial, but if students are willing to learn techniques in this area not necessarily required. In terms of course work, CS61A is likely required. CS61B is preferred. An upper division analysis class (CS70, DATA 100, or equivalent) would also be preferred for data analysis and inference. Machine learning experience preferred for sub-project 3. Other statistical background may also be helpful, especially experience with discontinuity designs.

Weekly Hours: to be negotiated

Off-Campus Research Site: remote